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Dissertations / Theses on the topic 'Relational databases'
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1
Bielecki, Pavel. "Distributed relational database system of occasionally connected databases." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2000. http://handle.dtic.mil/100.2/ADA378092.
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Kitinya, Sylivano Chiluli Nonga. "Relational multimedia databases." Thesis, Durham University, 1987. http://etheses.dur.ac.uk/1242/.
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This thesis is concerned with the design and im plementation of a Relational Multimedia Database System, in short RMDBS. RMDBS is designed to efficiently use storage space and manipulate various kinds of data; attribute data, bit-m apped pictures, and program s in binary code. RMDBS is an integrated system which enables the user to manage and control operations on the different forms of data in a user friendly manner. This means that even nonexperienced users can work with the system. The work described in this thesis is novel in that a true multimedia database has been implemented within the framework of a traditional relational DBMS. Previous work in this area has concentrated either in building data base management systems for storing picture-based data or multimedia databases which are not true data base management systems. RMDBS is implemented using the Revelation data base management system.
3
Alkahtani, Mufleh M. "Modeling relational database management systems." Virtual Press, 1993. http://liblink.bsu.edu/uhtbin/catkey/865955.
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Almost all of the database products developed over the past few years are based on what is called the relational approach.The purpose of this thesis is to characterize a relational data base management system, we do this by studying the relational model in some depth.The relational model is not static, rather it has been evolving over time. We trace the evolution of the relational model. We will also consider the ramifications of the relational model for modern database systems.<br>Department of Computer Science
4
Karlapalem, Kamalakar. "Redesign of distributed relational databases." Diss., Georgia Institute of Technology, 1992. http://hdl.handle.net/1853/9173.
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Zavodny, Jakub. "Factorisation in relational databases." Thesis, University of Oxford, 2014. http://ora.ox.ac.uk/objects/uuid:54c9a3a7-caac-40d9-90fb-83797ced9c5a.
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We study representation systems for relational data based on relational algebra expressions with unions, products, and singleton relations. Algebraic factorisation using the distributivity of product over union allows succinct representation of many-to-many relationships; further succinctness is brought by sharing repeated subexpressions. We show that these techniques are especially applicable to results of conjunctive queries. In the first part of the dissertation we derive tight asymptotic size bounds for two flavours of factorised representations of results of conjunctive queries. Any conjunctive query is characterised by rational parameters that govern the factorisability of its results independently of the database instance. We relate these parameters to fractional edge covers and fractional hypertree decompositions. Factorisation naturally extends from relational data to its provenance. We characterise conjunctive queries by tight bounds on their readability, which captures how many times each input tuple is used to contribute to an output tuple, and we define syntactically the class of queries with bounded readability. In the second part of the dissertation we describe FDB, a relational database engine that uses factorised representations at the physical layer to reduce data redundancy and boost query performance. We develop algorithms for optimisation and evaluation of queries with selection, projection, join, aggregation and order-by clauses on factorised representations. By introducing novel operators for factorisation restructuring and a new optimisation objective to maintain intermediate and final results succinctly factorised, we allow query evaluation with lower time complexity than on flat relations. Experiments show that for data sets with many-to-many relationships, FDB can outperform relational engines by orders of magnitude.
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Sullivan, Larry. "Performance issues in mid-sized relational database machines /." Online version of thesis, 1989. http://hdl.handle.net/1850/10445.
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Jermaine, Christopher. "Approximate answering of aggregate queries in relational databases." Diss., Georgia Institute of Technology, 2002. http://hdl.handle.net/1853/9221.
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Chen, Yu 1979. "Data mining relational databases with probabilistic relational models." Thesis, McGill University, 2006. http://digitool.Library.McGill.CA:80/R/?func=dbin-jump-full&object_id=97928.
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Relational databases are a popular method for organizing and storing data. Unfortunately, many machine-learning techniques are unable to handle complex relational models. The Probabilistic Relational Model (PRM) is an extension of the Bayesian Network framework that can express relational structure as well as probabilistic dependencies. In this thesis, we significantly expand and improve an implementation of PRMs that allows defining conditional probability distributions over discrete and continuous variables. The thesis uses as starting point an implementation that has various problems, and runs very slowly when using a database management system (DBMS) as storage. This thesis discusses alternative algorithms that improve the accuracy of the learned models, the computing performance, and correct the inference problems of the existing implementation. The focus is on techniques used to reduce the running time of the algorithms when the implementation is used to learn from data stored on a DBMS. The thesis provides experimental results using this package on both synthetic and real data sets.
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Henderson, Rebecca Sue. "Technology in action : the design and use of relational databases /." Thesis, Connect to this title online; UW restricted, 1999. http://hdl.handle.net/1773/8880.
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Monat, Andre Soares. "Exceptional values in relational databases." Thesis, University of East Anglia, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.359326.
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MORELLI, EDUARDO MARIA TERRA. "AUTOMATIC REINDEXING IN RELATIONAL DATABASES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2006. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=9531@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>Uma dentre as muitas tarefas desempenhadas por DBAs
consiste em tentar
garantir que os tempos de respostas dos comandos
submetidos por usuários a um
grande SGBDR não excedam valores previamente acordados.
Esta dissertação
segue uma linha de estudos denominada auto-sintonia de
índices, que preconiza a
realização de ajustes automáticos na execução de consultas
SQL, visando reduzirlhes
tempos de resposta, a partir de alterações no conjunto de
índices: criação,
eliminação e recriação. Este trabalho teve como ponto de
partida a dissertação de
Marcos Salles [32], que seguiu a mesma linha, propondo um
mecanismo
automático de criação de índices. Esta dissertação estende
[32], primeiro
submetendo sua implementação a uma carga de trabalho
alternativa e depois
realizando eliminações e reconstruções de índices
automáticas, levando em
consideração níveis de preenchimento de páginas
alternativos. Também foram
realizados testes utilizando ferramentas comerciais,
Oracle 10g e SQL Server
2005, para avaliar quão eficaz comportou-se a
implementação proposta em [32].
Vale ressaltar que os testes realizados limitaram-se à
criação de índices, já que as
ferramentas não oferecem facilidades de reconstrução
automática. Diferentemente
dos trabalhos publicados nessa linha de estudos e das
ferramentas comerciais
disponíveis, foi criado um protótipo que não se limita a
sugerir novos índices;
também são eliminados os que deixaram de ser
interessantes, porém, antes ocorre
uma avaliação para verificar se a reconstrução não seria
mais adequada. Criou-se,
inclusive, uma heurística rudimentar que avalia um índice
a ser destruído e
recomenda sua reconstrução, caso atenda a determinados
requisitos.<br>One of the most important tasks of Database Administrators
certainly is to
guarantee optimal response times to statements submitted
by users of big
RDBMS. Our dissertation deals with Index Self-tuning,
which means creating,
dropping or recreating indexes automatically, in order to
decrease SQL queries
durations. We start from Marcos Salles´ dissertation [32],
which proposed an
automatic way of creating indexes. We extend [32] in many
ways: first using a
different workload, TPC-H like. Second, following created
indexes inspecting its
usage. Finally, we have gotten to drop and, mostly,
recreate indexes using
different fillfactor in leaf pages. Also, we have
elaborated many tests using
commercial tools, Microsoft SQL Server 2005 and Oracle 10g
in order to ratify
[32] ideas. Unfortunatelly, we could not test automatic
dropping and recreating in
these tools, as long as they do not offer this kind of
functionalities. Unlike related
work and commercial tools, we have created a code
prototype that not only
suggests new indexes creations, but also drops and
recreates indexes using an own
heuristics. To validate our ideas we have used a TPC-C
like workload, but we had
to make some changes to increase updates and force
reindexing.
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Rawlani, Praynaa. "Graph analytics on relational databases." Thesis, Massachusetts Institute of Technology, 2014. http://hdl.handle.net/1721.1/100670.
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Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2014.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (pages 99-100).<br>Graph analytics has become increasing popular in the recent years. Conventionally, data is stored in relational databases that have been refined over decades, resulting in highly optimized data processing engines. However, the awkwardness of expressing iterative queries in SQL makes the relational query-processing model inadequate for graph analytics, leading to many alternative solutions. Our research explores the possibility of combining a more natural query model with relational databases for graph analytics. In particular, we bring together a graph-natural vertex-centric query interface to highly optimized column-oriented relational databases, thus providing the efficiency of relational engines and ease-of-use of new graph systems. Throughout the thesis, we used stochastic gradient descent, a loss-minimization algorithm applied in many machine learning and graph analytics queries, as the example iterative algorithm. We implemented two different approaches for emulating a vertex-centric interface on a leading column-oriented database, Vertica: disk-based and main-memory based. The disk-based solution stores data for each iteration in relational tables and allows for interleaving SQL queries with graph algorithms. The main-memory approach stores data in memory, allowing faster updates. We applied optimizations to both implementations, which included refining logical and physical query plans, applying algorithm-level improvements and performing system-specific optimizations. The experiments and results show that the two implementations provide reasonable performance in comparison with popular graph processing systems. We present a detailed cost analysis of the two implementations and study the effect of each individual optimization on the query performance.<br>by Praynaa Rawlani.<br>M. Eng.
13
Maatuk, Abdelsalam. "Migrating relational databases into object-based and XML databases." Thesis, Northumbria University, 2009. http://nrl.northumbria.ac.uk/3374/.
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Rapid changes in information technology, the emergence of object-based and WWW applications, and the interest of organisations in securing benefits from new technologies have made information systems re-engineering in general and database migration in particular an active research area. In order to improve the functionality and performance of existing systems, the re-engineering process requires identifying and understanding all of the components of such systems. An underlying database is one of the most important component of information systems. A considerable body of data is stored in relational databases (RDBs), yet they have limitations to support complex structures and user-defined data types provided by relatively recent databases such as object-based and XML databases. Instead of throwing away the large amount of data stored in RDBs, it is more appropriate to enrich and convert such data to be used by new systems. Most researchers into the migration of RDBs into object-based/XML databases have concentrated on schema translation, accessing and publishing RDB data using newer technology, while few have paid attention to the conversion of data, and the preservation of data semantics, e.g., inheritance and integrity constraints. In addition, existing work does not appear to provide a solution for more than one target database. Thus, research on the migration of RDBs is not fully developed. We propose a solution that offers automatic migration of an RDB as a source into the recent database technologies as targets based on available standards such as ODMG 3.0, SQL4 and XML Schema. A canonical data model (CDM) is proposed to bridge the semantic gap between an RDB and the target databases. The CDM preserves and enhances the metadata of existing RDBs to fit in with the essential characteristics of the target databases. The adoption of standards is essential for increased portability, flexibility and constraints preservation. This thesis contributes a solution for migrating RDBs into object-based and XML databases. The solution takes an existing RDB as input, enriches its metadata representation with the required explicit semantics, and constructs an enhanced relational schema representation (RSR). Based on the RSR, a CDM is generated which is enriched with the RDB's constraints and data semantics that may not have been explicitly expressed in the RDB metadata. The CDM so obtained facilitates both schema translation and data conversion. We design sets of rules for translating the CDM into each of the three target schemas, and provide algorithms for converting RDB data into the target formats based on the CDM. A prototype of the solution has been implemented, which generates the three target databases. Experimental study has been conducted to evaluate the prototype. The experimental results show that the target schemas resulting from the prototype and those generated by existing manual mapping techniques were comparable. We have also shown that the source and target databases were equivalent, and demonstrated that the solution, conceptually and practically, is feasible, efficient and correct.
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Moatassem, Nawal N. "A Study of Migrating Biological Data from Relational Databases to NoSQL Databases." Youngstown State University / OhioLINK, 2015. http://rave.ohiolink.edu/etdc/view?acc_num=ysu1442486094.
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Yu, Chaoran. "A study on relational databases through mathematical theories of relations and logic." Virtual Press, 1988. http://liblink.bsu.edu/uhtbin/catkey/539627.
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The purpose of this study is to explore that mathematics provides a convenient formalism for studying classical database management system problems. There are two main parts in this study, devoted respectively to using mathematical theory of relations and using logical theory to study database management systems. In the first part we focus on relational model and relational algebra. The second part deals with the application of mathematical logic to database management systems, where logic may be used both as a inference system and as a representation language. The features and logical mechanisms of Prolog programming language have been studied. A sample logical database model is developed and tested, using the logic programming language Prolog.<br>Department of Computer Science
16
Hansson, Andreas. "Relational Database Web Application : Web administration interface for visualizing and predicting relationships to manage relational databases." Thesis, Mittuniversitetet, Avdelningen för informations- och kommunikationssystem, 2015. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-25879.
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There is a need of storing and keeping track of things. As the amount of information increases, so does the demand for suitable applications that can manage the data. This thesis has had its focus on developing a web administration interface for relational databases, where the focus has been on managing and visualizing the data, where relationships between data within the database could be predicted through an algorithm. During the thesis, it was revealed that administrators can utilize naming conventions for databases, a property which can be used to predict its relationships. Furthermore, existing applications for managing databases has been compared with the thesis' implementation. Notable differences are that existing solutions are focused towards the structure of the data, rather than the data itself. To accomplish all this, an agile method was chosen for fast results within the deadline, together with standardized web development tools and JavaScript frameworks. The resulting implementation consists of a front- and backend. The frontend was developed using the Ember.JS framework for making web applications and the backend was implemented using Node.JS, together with a component for handling different database dialects called Sequelize. It has been concluded that the prototype this thesis has resulted in works as a proof of concept, complete with a prediction algorithm that can suggest relationships within databases that utilizes convenient and consistent naming conventions. In the future, further research and tests could be conducted to evaluate the security, reliability and usability of the application, to ensure its production quality.
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Aleksic, Mario. "Incremental computation methods in valid and transaction time databases." Thesis, Georgia Institute of Technology, 1996. http://hdl.handle.net/1853/8126.
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Hines, Gary L. "From entities to objects : reverse engineering a relational data model into an object-oriented design." Virtual Press, 2000. http://liblink.bsu.edu/uhtbin/catkey/1164846.
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In many software applications, an object-oriented design (OOD) is generated first, then persistent storage is implemented by mapping the objects to a relational database. This thesis explores the "reverse engineering" of an OOD out of an existing relational data model. Findings from the current literature are presented, and a case study is undertaken using the model and research process published by GENTECH, a nonprofit organization promoting genealogical computing. The model is mapped into an OOD and captured in Unified Modeling Language (UML) class diagrams and object collaboration diagrams. The suitability of the example OOD is evaluated against the GENTECH research process using UML use cases and sequence diagrams. The mapping of relational database designs into OODs is found to be suitable in certain instances.<br>Department of Computer Science
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Ulibarri, Desirea Duarte. "Volunteer system project Regis University Networking Lab Practicum /." [Denver, Colo.] : Regis University, 2006. http://165.236.235.140/lib/DUlibarriPartI2006.pdf.
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Ciolek, Thomas S. "Meeting the challenges of met data with MySQL X /." [Denver, Colo.] : Regis University, 2006. http://165.236.235.140/lib/TCiolek2006.pdf.
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Attar-Bashi, Hussain Ali. "Natural language output from relational databases." Thesis, University of Bradford, 1990. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.304029.
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Kesztyus, Tibor I., and Klaus P. Kratzer. "Three-dimensional visualization of relational databases." Journal for New Generation Sciences, Vol 2, Issue 1: Central University of Technology, Free State, Bloemfontein, 2004. http://hdl.handle.net/11462/451.
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Published Article<br>In recent years, databases have reached unprecedented complexity and volume. A database structure comprising tens of thousands of tables with a staggering number of inter-table relationships to match can hardly be understood and managed by the human mind. This holds in particular, if two-dimensional visualizations of such a structure are used. This paper describes a project to enhance human comprehension by another dimension enabling database users to move among database tables in three dimensions. The project applies techniques of virtual reality enabling users to control the individual aspect and the level of detail while gaining valuable insights into the structure, the contents, and the retrieval strategies within their databases.
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Herath, H. M. A. C. "Statistical databases within a relational framework." Thesis, Keele University, 1994. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.386218.
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Clemens, David W. "Relational database design of a shipboard ammunition inventory, requisitioning, and reporting system." Thesis, Monterey, California : Naval Postgraduate School, 1990. http://handle.dtic.mil/100.2/ADA231559.
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Thesis (M.S. in Information Systems)--Naval Postgraduate School, June 1990.<br>Thesis Advisor(s): Kamel, Magdi N. Second Reader: Bhargava, Hemant K. "June 1990." Description based on signature page as viewed on October 19, 2009. Author(s) subject terms: Ammunition, database design, relational database. Includes bibliographical references (p. 163-166). Also available online.
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Nagy, Victor. "Performance Analysis of Relational Databases, Object-Oriented Databases and ORM Frameworks." Thesis, Högskolan i Skövde, Institutionen för informationsteknologi, 2014. http://urn.kb.se/resolve?urn=urn:nbn:se:his:diva-9528.
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In the planning stage of web and software development, it is important to select the right tool for the job. When selecting the database to use, relational databases like MySQL is a popular choice. However, relational databases suffer by object-relational impedance mismatch. In this work we will explore the response time of relational and object-oriented databases and the overhead of ORM frameworks. This will be done by creating a web application that receives data about flights and airports from a client, which measures the response time of the databases and the entire request. It was found that MySQL has the lowest response time, while the ORM framework Hibernate adds an overhead on some of the tests while performing similar to MySQL. Db4o had the highest response time in a majority of the tests. In future works, this study could be extended by other tests or by other type of databases.
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Frank, Martin Robert. "Adaptive and automated index selection in relational database systems." Thesis, Georgia Institute of Technology, 1991. http://hdl.handle.net/1853/8170.
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Stanier, C. F. "A model integrity based object-relational data model and complex data model definition framework." Thesis, Staffordshire University, 2009. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.522119.
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Jafer, Yasser. "Aggregation and Privacy in Multi-Relational Databases." Thèse, Université d'Ottawa / University of Ottawa, 2012. http://hdl.handle.net/10393/22695.
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Most existing data mining approaches perform data mining tasks on a single data table. However, increasingly, data repositories such as financial data and medical records, amongst others, are stored in relational databases. The inability of applying traditional data mining techniques directly on such relational database thus poses a serious challenge. To address this issue, a number of researchers convert a relational database into one or more flat files and then apply traditional data mining algorithms. The above-mentioned process of transforming a relational database into one or more flat files usually involves aggregation. Aggregation functions such as maximum, minimum, average, standard deviation, count and sum are commonly used in such a flattening process.
Our research aims to address the following question: Is there a link between aggregation and possible privacy violations during relational database mining? In this research we investigate how, and if, applying aggregation functions will affect the privacy of a relational database, during supervised learning, or classification, where the target concept is known. To this end, we introduce the PBIRD (Privacy Breach Investigation in Relational Databases) methodology. The PBIRD methodology combines multi-view learning with feature selection, to discover the potentially dangerous sets of features as hidden within a database. Our approach creates a number of views, which consist of subsets of the data, with and without aggregation. Then, by identifying and investigating the set of selected features in each view, potential privacy breaches are detected. In this way, our PBIRD algorithm is able to discover those features that are correlated with the classification target that may also lead to revealing of sensitive information in the database.
Our experimental results show that aggregation functions do, indeed, change the correlation between attributes and the classification target. We show that with aggregation, we obtain a set of features which can be accurately linked to the classification target and used to predict (with high accuracy) the confidential information. On the other hand, the results show that, without aggregation we obtain another different set of potentially harmful features. By identifying the complete set of potentially dangerous attributes, the PBIRD methodology provides a solution where the database designers/owners can be warned, to subsequently perform necessary adjustments to protect the privacy of the relational database.
In our research, we also perform a comparative study to investigate the impact of aggregation on the classification accuracy and on the time required to build the models. Our results suggest that in the case where a database consists only of categorical data, aggregation should especially be used with caution. This is due to the fact that aggregation causes a decrease in overall accuracies of the resulting models. When the database contains mixed attributes, the results show that the accuracies without aggregation and with aggregation are comparable. However, even in such scenarios, schemas without aggregation tend to slightly outperform. With regard to the impact of aggregation on the model building time, the results show that, in general, the models constructed with aggregation require shorter building time. However, when the database is small and consists of nominal attributes with high cardinality, aggregation causes a slower model building time.
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Zimanyi, Esteban. "Incomplete and uncertain information in relational databases." Doctoral thesis, Universite Libre de Bruxelles, 1992. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/212914.
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<p align="justify">In real life it is very often the case that the available knowledge is imperfect in the sense that it represents multiple possible states of the external world, yet it is unknown which state corresponds to the actual situation of the world. Imperfect knowledge can be of two different categories. Knowledge is incomplete if it represents different states, one of which is true in the external world. On the contrary, knowledge is uncertain if it represents different states which may be satisfied or are likely to be true in the external world.</p><p><p align="justify">Imperfect knowledge can be considered under two different perspectives: using either an algebraic or a logical approach. We present both approaches in relation with the standard relational model, providing the necessary background for the subsequent development.</p><p><p align="justify">The study of imperfect knowledge has been an active area of research, in particular in the context of relational databases. However, due to the complexity of manipulating imperfect knowledge, little practical results have been obtained so far. In this thesis we provide a survey of the field of incompleteness and uncertainty in relational databases;it can be used also as an introductory tutorial for understanding the intuitive semantics and the problems encountered when representing and manipulating such imperfect knowledge. The survey concentrates in giving an unifying presentation of the different approaches and results found in the literature, thus providing a state of the art in the field.</p><p><p align="justify">The rest of the thesis studies in detail the manipulation of one type of incomplete knowledge, namely disjunctive information, and one type of uncertain knowledge, namely probabilistic information. We study both types of imperfect knowledge using similar approaches, that is through an algebraic and a logical framework. The relational algebra operators are generalized for disjunctive and probabilistic relations, and we prove the correctness of these generalizations. In addition, disjunctive and probabilistic databases are formalized using appropriate logical theories and we give sound and complete query evaluation algorithms.</p><p><p align="justify">A major implication of these studies is the conviction that viewing incompleteness and uncertainty as different facets of the same problem would allow to achieve a deeper understanding of imperfect knowledge, which is absolutely necessary for building information systems capable of modeling complex real-life situations. </p><br>Doctorat en sciences, Spécialisation Informatique<br>info:eu-repo/semantics/nonPublished
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Ellison, Martyn. "Evaluating cloud migration options for relational databases." Thesis, University of York, 2017. http://etheses.whiterose.ac.uk/20206/.
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Migrating the database layer remains a key challenge when moving a software system to a new cloud provider. The database is often very large, poorly documented, and used to store business-critical information. Most cloud providers offer a variety of services for hosting databases and the most suitable choice depends on the database size, workload, performance requirements, cost, and future business plans. Current approaches do not support this decision-making process, leading to errors and inaccurate comparisons between database migration options. The heterogeneity of databases and clouds means organisations often have to develop their own ad-hoc process to compare the suitability of cloud services for their system. This is time consuming, error prone, and costly. This thesis contributes to addressing these issues by introducing a three-phase methodology for evaluating cloud database migration options. The first phase defines the planning activities, such as, considering downtime tolerance, existing infrastructure, and information sources. The second phase is a novel method for modelling the structure and the workload of the database being migrated. This addresses database heterogeneity by using a multi-dialect SQL grammar and annotated text-to-model transformations. The final phase consumes the models from the second and uses discrete-event simulation to predict migration cost, data transfer duration, and cloud running costs. This involved the extension of the existing CloudSim framework to simulate the data transfer to a new cloud database. An extensive evaluation was performed to assess the effectiveness of each phase of the methodology and of the tools developed to automate their main steps. The modelling phase was applied to 15 real-world systems, and compared to the leading approach there was a substantial improvement in: performance, model completeness, extensibility, and SQL support. The complete methodology was applied to four migrations of two real-world systems. The results from this showed that the methodology provided significantly improved accuracy over existing approaches.
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El, Abri Marwa. "Probabilistic relational models learning from graph databases." Thesis, Nantes, 2018. http://www.theses.fr/2018NANT4019/document.
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Historiquement, les Modèles Graphiques Probabilistes (PGMs) sont une solution d’apprentissage à partir des données incertaines et plates, appelées aussi données propositionnelles ou représentations attribut-valeur. Au début des années 2000, un grand intérêt a été adressé au traitement des données relationnelles présentant un grand nombre d’objets participant à des différentes relations. Les Modèles Probabilistes Relationnels (PRMs) présentent une extension des PGMs pour le contexte relationnel. Avec l’évolution rapide issue de l’internet, des innovations technologiques et des applications web, les données sont devenues de plus en plus variées et complexes. D’où l’essor du Big Data. Plusieurs types de bases de données ont été créés pour s’adapter aux nouvelles caractéristiques des données, dont les plus utilisés sont les bases de données graphe. Toutefois, tous les travaux d’apprentissage des PRMs sont consacrés à apprendre à partir des données bien structurées et stockées dans des bases de données relationnelles. Les bases de données graphe sont non structurées et n’obéissent pas à un schéma bien défini. Les arcs entre les noeuds peuvent avoir des différentes signatures. En effet, les relations qui ne correspondent pas à un modèle ER peuvent exister dans l'instance de base de données. Ces relations sont considérées comme des exceptions. Dans ce travail de thèse, nous nous intéressons à ce type de bases de données. Nous étudions aussi deux types de PRMs à savoir, Direct Acyclic Probabilistic Entity Relationship (DAPER) et chaines de markov logiques (MLNs). Nous proposons deux contributions majeures. Premièrement, Une approche d’apprentissage des DAPERs à partir des bases de données graphe partiellement structurées. Une deuxième approche consiste à exploiter la logique de premier ordre pour apprendre les DAPERs en utilisant les MLNs pour prendre en considération les exceptions qui peuvent parvenir lors de l’apprentissage. Nous menons une étude expérimentale permettant de comparer nos méthodes proposées avec les approches déjà existantes<br>Historically, Probabilistic Graphical Models (PGMs) are a solution for learning from uncertain and flat data, also called propositional data or attributevalue representations. In the early 2000s, great interest was addressed to the processing of relational data which includes a large number of objects participating in different relations. Probabilistic Relational Models (PRMs) present an extension of PGMs to the relational context. With the rise of the internet, numerous technological innovations and web applications are driving the dramatic increase of various and complex data. Consequently, Big Data has emerged. Several types of data stores have been created to manage this new data, including the graph databases. Recently there has been an increasing interest in graph databases to model objects and interactions. However, all PRMs structure learning use wellstructured data that are stored in relational databases. Graph databases are unstructured and schema-free data stores. Edges between nodes can have various signatures. Since, relationships that do not correspond to an ER model could be depicted in the database instance. These relationships are considered as exceptions. In this thesis, we are interested by this type of data stores. Also, we study two kinds of PRMs namely, Direct Acyclic Probabilistic Entity Relationship (DAPER) and Markov Logic Networks (MLNs). We propose two significant contributions. First, an approach to learn DAPERs from partially structured graph databases. A second approach consists to benefit from first-order logic to learn DAPERs using MLN framework to take into account the exceptions that are dropped during DAPER learning. We are conducting experimental studies to compare our proposed methods with existing approaches
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Nulty, William Glenn. "Geometric searching with spacefilling curves." Diss., Georgia Institute of Technology, 1993. http://hdl.handle.net/1853/24520.
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Khayundi, Peter. "A comparison of open source object-oriented database products." Thesis, University of Fort Hare, 2009. http://hdl.handle.net/10353/254.
Full textAbstract:
Object oriented databases have been gaining popularity over the years. Their ease of use and the advantages that they offer over relational databases have made them a popular choice amongst database administrators. Their use in previous years was restricted to business and administrative applications, but improvements in technology and the emergence of new, data-intensive applications has led to the increase in the use of object databases. This study investigates four Open Source object-oriented databases on their ability to carry out the standard database operations of storing, querying, updating and deleting database objects. Each of these databases will be timed in order to measure which is capable of performing a particular function faster than the other.
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Lau, Ho Lam. "The development of the nested relational sequence model to support XML databases /." View Abstract or Full-Text, 2002. http://library.ust.hk/cgi/db/thesis.pl?COMP%202002%20LAU.
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Thesis (M. Phil.)--Hong Kong University of Science and Technology, 2002.<br>Includes bibliographical references (leaves 87-96). Also available in electronic version. Access restricted to campus users.
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Toprak, Serkan. "Data Mining For Rule Discovery In Relational Databases." Master's thesis, METU, 2004. http://etd.lib.metu.edu.tr/upload/12605356/index.pdf.
Full textAbstract:
Data is mostly stored in relational databases today. However, most data mining algorithms are not capable of working on data stored in relational databases directly. Instead they require a preprocessing step for transforming relational data into algorithm specified form. Moreover, several data mining algorithms provide solutions for single relations only. Therefore, valuable hidden knowledge involving multiple relations remains undiscovered. In this thesis, an implementation is developed for discovering multi-relational association rules in relational databases. The implementation is based on a framework providing a representation of patterns in relational databases, refinement methods of patterns, and primitives for obtaining necessary record counts from database to calculate measures for patterns. The framework exploits meta-data of relational databases for pruning search space of patterns. The implementation extends the
framework by employing Apriori algorithm for further pruning the search space and discovering relational recursive patterns. Apriori algorithm is used for finding large itemsets of tables, which are used to refine patterns. Apriori algorithm is modified by changing support calculation method for itemsets. A method
for determining recursive relations is described and a solution is
provided for handling recursive patterns using aliases. Additionally, continuous attributes of tables are discretized utilizing equal-depth partitioning. The implementation is
tested with gene localization prediction task of KDD Cup 2001 and
results are compared to those of the winner approach.
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Lee, Anna. "Transformation of set schema into relational structures." Thesis, University of British Columbia, 1987. http://hdl.handle.net/2429/26431.
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This thesis describes a new approach of relational database design using the SET conceptual model. The SET conceptual model is used for information modelling. The database schema generated from the information modelling is called the SET schema. The SET schema consists of the declarations of all the sets of the database schema. A domain graph can be constructed based on the information declared in the SET schema. A domain graph is a directed graph with nodes labelled with declared sets and arcs labelled with degree information. Each are in the domain graph points to a node S from a node labelled with an immediate domain predecessor of S. The new method of table design for the relational database involves partitioning the domain graph into mutually exclusive <1,1>-connected components based on the degree information. These components (subgraphs) are then transformed into tree structures.
These trees are extended to include the domain predecessors of their nodes to make them predecessor total. The projections of these extended trees into the value sets labelling their leaf nodes form a set of relations which can be represented by tables. This table design method is described and presented in this thesis, along with d program that automates the method. Given a schema of the SET model, together with some degree information about defined sets that a user must calculate based on the intention of the defined sets, the program produces a relational database schema that will record data for the SET schema correctly and completely.<br>Science, Faculty of<br>Computer Science, Department of<br>Graduate
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Markowetz, Alexander. "Keyword search over relational data /." View abstract or full-text, 2008. http://library.ust.hk/cgi/db/thesis.pl?CSED%202008%20MARKOW.
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Hedman, Surlien Peter. "Economic advantages of Blockchain technology VS Relational database : An study focusing on economic advantages with Blockchain technology and relational databases." Thesis, Blekinge Tekniska Högskola, Institutionen för industriell ekonomi, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-17366.
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Many IT-systems are when created not designed to be flexible and dynamic resulting in old and complex systems hard to maintain. Systems usually build their functionality and capability on the data contained in their databases. The database underlines such system, and when data do not correspond between different and synchronizing systems, it is a troublesome debugging process. This is because systems are complex and the software architecture is not always easy to understand. Due to increasing complexity in systems over time, making systems harder to debug and understand, there is a need for a system that decreases debugging costs. Furthermore, result in better transaction costs. This study proposes a system based on blockchain technology to accomplish this. An ERP system based on blockchain with encrypted transactions was constructed to determine if the proposed system can contribute in better transaction costs. A case study at multiple IT-companies and comparison to an existing ERP system module validated the system. A successful simulation showed that multiple parts could read and append data to an immutable storage system for one truth of data. By all counts, and with proven results, the constructed blockchain solution based on encrypted transactions for an ERP system can reduce debugging costs. It is also shown that a centralized database structure where external and internal systems can get one truth of data, decreases transaction costs. However, it is the decision makers in companies that need to be convinced for the constructed system to be implemented. A problem is also when modifications to the object type, then historical transactions cannot be changed in an immutable storage solution. Blockchain is still a new technology, and the knowledge of the technology and the evolution of the system determines if the proposed software architecture will result in better transaction costs.
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Norcio, Sheila Azadeh. "Object-oriented and relational databases : a comparative study of concepts and applications /." Master's thesis, This resource online, 1990. http://scholar.lib.vt.edu/theses/available/etd-01202010-020128/.
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Krogel, Mark-André. "On propositionalization for knowledge discovery in relational databases." [S.l. : s.n.], 2005. http://deposit.ddb.de/cgi-bin/dokserv?idn=976835835.
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To, Christina. "A form of manipulation system for relational databases." Thesis, University of Ottawa (Canada), 1987. http://hdl.handle.net/10393/5411.
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Luo, Yi Computer Science & Engineering Faculty of Engineering UNSW. "SPARK: a keyword search system on relational databases." Awarded by:University of New South Wales. Computer Science & Engineering, 2009. http://handle.unsw.edu.au/1959.4/41542.
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With the increasing usage of storing textual data into relational databases, there is a demand for the databases to support keyword queries over textual data. Due to the normalization and the inherent connections among tuples in different tables, traditional IR-style ranking and query evaluation methods do not apply. A number of systems have been proposed to deal with this issue. In this thesis, I will give a detailed demonstration and description to our SPARK project. In the project, we study both the effectiveness and the efficiency issues of answering top-k keyword query on a relational database system. We propose a new ranking formula by adapting existing IR techniques on a natural notion of ???virtual document???. Compared with previous approaches, our new ranking method is simple yet effective, and agrees with human being???s perception better. We also study efficient query processing methods based on the new ranking method, and propose algorithms that have minimal accesses to the database. We have conducted extensive experiments on large-scale real databases using two popular RDBMSs. The experimental results demonstrate significant improvement to the alternative approaches in terms of both retrieval effectiveness and efficiency. We build a prototype of SPARK system on top of popular RDBMS based on these new techniques to satisfy different kinds of users and to support various query modes.
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Vista, Dimitra. "Optimizing incremental view maintenance expressions in relational databases." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1997. http://www.collectionscanada.ca/obj/s4/f2/dsk2/tape16/PQDD_0015/NQ28310.pdf.
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Owda, Majdi Sabe. "Conversation-based interfaces to relational databases (C-BIRDS)." Thesis, Manchester Metropolitan University, 2012. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.551122.
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The development of reliable natural language interfaces to relational databases can accelerate the progress of many areas of applications, such as the need for interactive relational database interfaces for non-technical users. This thesis presents a novel development of C-BIRDs framework. The C-BIRD framework was developed in two phases. The first phase involved the development of a Static Approach-Based C-BIRD framework, which is based on a combination of a Goal-Oriented Conversational Agent (GOCA) and a knowledge tree (KT). GO CAs have proven their capability to disambiguate the user's needs through natural language conversations. KT is used to overcome the lack of connectivity between the GOCA and the relational database, through organizing the domain knowledge in a knowledge tree. In addition the Static Approach-Based C-BIRD framework, a number of strategies were employed based on scripting structures in order to enhance the reasoning capabilities towards answering user queries. The second phase involved the development of a Dynamic Approach- Based C-BIRD framework which is based on information extraction (lE) in order to dynamically create an SQL statement that answers user queries. lE component utilised a number of SQL query templates, which are made of relational database semantically understandable patterns such as table and column names. In addition, the dynamic approach used the conversational agent to disambiguate the dynamically generated SQL queries by confirming these queries with the user by means of SQL template specific strategies scripts. The Static Approach-Based C-BIRD prototype showed excellent results in terms of successfully mapping natural language conversations into SQL statements (i.e. task success, in which 5 tasks performed by 20 participants with an overall result of 91 %). The dynamic approach also showed very good results in terms of task success; 5 tasks performed by 20 participants with an overall result came to 74%. In summary, the proposed static approach C-BIRD framework offered a novel methodology to develop reliable conversational interfaces to relational databases in which engineered queries can be answered. In addition, the dynamic approach introduced a novel way to map natural language utterances into SQL statements and confirming the results with the user, before providing the final answer. Ultimately, the user experiences a real-time and friendly conversational interface with the relational.
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BERARDI, RITA CRISTINA GALARRAGA. "DESIGN RATIONALE IN THE TRIPLIFICATION OF RELATIONAL DATABASES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2015. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=27082@1.
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PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICO<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>DOUTORADO SANDUÍCHE NO EXTERIOR<br>Uma das estratégias mais populares para publicar dados estruturados na Web é
expor bases de dados relacionais (BDR) em formato RDF. Esse processo é
chamado BDR-para-RDF ou triplificação. Além disto, princípios de Linked Data
oferecem vários guias para dar suporte a este processo. Existem duas principais
abordagens para mapear bases de dados relacionais para RDF: (1) a abordagem de
mapeamento direto, onde o esquema das bases de dados é diretamente mapeado
para um esquema RDF, e (2) a abordagem de mapeamento customizado, onde o
esquema RDF pode ser significativamente diferente do esquema original da base
de dados relacional. Em ambas abordagens, existem vários desafios relacionados
tanto com a publicação quanto com o uso de dados em RDF originados de bases
de dados relacionais. Esta tese propõe a coleta de design rationale como uma
valiosa fonte de informação para minimizar os desafios do processo de
triplificação. Essencialmente, a coleta de design rationale melhora a consciência
sobre as ações feitas no mapeamento da base de dados relacional para um
conjunto de dados no formato RDF. As principais contribuições da tese são: (1)
um modelo de design rationale (DR) adequado para o processo de BDR-para-
RDF, independente da abordagem utilizada (direta ou customizada); (2) a
integração de um modelo de DR para um processo que segue a abordagem direta
de BDR-para-RDF e para um processo que segue a abordagem customizada
usando a linguagem R2RML; (3) o uso do DR coletado para melhorar
recomendações de reuso de vocabulários existentes através de algoritmos de
Ontology Matching.<br>One of the most popular strategies to publish structured data on the Web is to
expose relational databases (RDB) in the RDF format. This process is called in
RDB-to-RDF or triplification. Furthermore, the Linked Data principles offer
useful guidelines for this process. Broadly stated, there are two main approaches
to map relational databases into RDF: (1) the direct mapping approach, where the
database schema is directly mapped to an RDF schema; and (2) the customized
mapping approach, where the RDF schema may significantly differ from the
original database schema. In both approaches, there are challenges related to the
publication and to the consumption of the published data. This thesis proposes the
capture of design rationale as a valuable source of information to minimize the
challenges in RDB-to-RDF processes. Essentially, the capture of design rationale
increases the awareness about the actions taken over the relational database to
map it as an RDF dataset. The main contributions of this thesis are: (1) a design
rationale (DR) model adequate to RDB-to-RDF processes, independently of the
approach (direct or customized) followed; (2) the integration of a DR model in an
RDB-to-RDF direct mapping process and in an RDB-to-RDF customized
mapping process using the R2RML language; (3) the use of the DR captured to
improve the recommendations for vocabularies to reuse.
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MEDEIROS, ANTONY SEABRA DE. "PARTITIONING AS A TUNING ACTION FOR RELATIONAL DATABASES." PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO, 2017. http://www.maxwell.vrac.puc-rio.br/Busca_etds.php?strSecao=resultado&nrSeq=30726@1.
Full textAbstract:
PONTIFÍCIA UNIVERSIDADE CATÓLICA DO RIO DE JANEIRO<br>COORDENAÇÃO DE APERFEIÇOAMENTO DO PESSOAL DE ENSINO SUPERIOR<br>PROGRAMA DE EXCELENCIA ACADEMICA<br>As principais estratégias de sintonia fina utilizadas por administradores de bancos de dados relacionais são a construção de estruturas de acesso, como índices, índices parciais e visões materializadas, e técnicas como desnormalização e reescrita de consultas. Estas técnicas e estruturas de acesso, juntas ou separadas, podem melhorar o desempenho das consultas submetidas ao banco de dados. O particionamento de tabelas do banco de dados, técnica tradicionalmente utilizada para distribuição de dados, também possui potencial para sintonia fina, pois permite que a varredura das tabelas seja realizada
somente nas partições que satisfazem os predicados das consultas. Mesmo em consultas com predicados de seletividade alta, cujos planos de execução frequentemente utilizam índices, o particionamento pode oferecer um benefício ainda maior. Esta dissertação de mestrado propõe avaliar o particionamento
como ação de sintonia fina de bancos de dados relacionais e, para tanto, desenvolve heurísticas para seleção de estratégias de particionamento e avaliação do seu benefício. Uma avaliação da qualidade dos resultados obtidos é realizada através de experimentos com um benchmark padrão para este tipo de pesquisa e mostramos que, em certos casos, é vantajoso particionar dados.<br>The main fine tuning strategies used by relational database administrators are the construction of access structures, such as indexes, partial indexes and materialized views, and techniques such as denormalization and query rewriting. These techniques and access structures, together or separately, can improve the performance of queries submitted to the database. Database partitioning, a technique traditionally used for data distribution, has also the potential for fine tuning, since it allows the scanning of tables to be performed only on partitions that satisfy query predicates. Even in queries with high selectivity predicates, whose execution plans often use indexes, partitioning can offer even greater benefit. This dissertation proposes to evaluate the partitioning as a fine tuning action of relational databases and, for that, develops heuristics for selection of partitioning strategies and evaluation of its benefit. An evaluation of the quality of the results obtained is carried out through experiments with a standard benchmark for this type of research and we have shown that, in certain cases, it is advantageous to partition data.
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Picalausa, Francois. "Guarded structural indexes: theory and application to relational RDF databases." Doctoral thesis, Universite Libre de Bruxelles, 2013. http://hdl.handle.net/2013/ULB-DIPOT:oai:dipot.ulb.ac.be:2013/209432.
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Ces dernières années ont vu un regain d’intérêt dans l’utilisation de données semi-structurées, grâce à la standardisation de formats d’échange de données sur le Web tels que XML et RDF. On notera en particulier le Linking Open Data Project qui comptait plus de 31 milliard de triplets RDF à la fin de l’année 2011. XML reste, pour sa part, l’un des formats de données privilégié de nombreuses bases de données de grandes tailles dont Uniprot, Open Government Initiative et Penn Treebank. <p><p>Cet accroissement du volume de données semi-structurées a suscité un intérêt croissant pour le développement de bases de données adaptées. Parmi les différentes approches proposées, on peut distinguer les approches relationnelles et les approches graphes, comme détaillé au Chapitre 3. Les premières visent à exploiter les moteurs de bases de données relationnelles existants, en y intégrant des techniques spécialisées. Les secondes voient les données semistructurées comme des graphes, c’est-à-dire un ensemble de noeuds liés entre eux par des arêtes étiquetées, dont elles exploitent la structure. L’une des techniques de ce domaine, connue sous le nom d’indexation structurelle, vise à résumer les graphes de données, de sorte à pouvoir identifier rapidement les données utiles au traitement d’une requête.<p><p>Les index structurels classiques sont construits sur base des notions de simulation et de bisimulation sur des graphes. Ces notions, qui sont d’usage dans de nombreux domaines tels que la vérification, la sécurité, et le stockage de données, sont des relations sur les noeuds des graphes. Fondamentalement, ces notions caractérisent le fait que deux noeuds partagent certaines caractéristiques telles qu’un même voisinage. <p><p>Bien que les approches graphes soient efficaces en pratique, elles présentent des limitations dans le cadre de RDF et son langage de requêtes SPARQL. Les étiquettes sont, dans cette optique, distinctes des noeuds du graphe .Dans le modèle décrit par RDF et supporté par SPARQL, les étiquettes et noeuds font néanmoins partie du même ensemble. C’est pourquoi, les approches graphes ne supportent qu’un sous-ensemble des requêtes SPARQL. Au contraire, les approches relationnelles sont fidèles au modèle RDF, et peuvent répondre au différentes requêtes SPARQL. <p><p>La question à laquelle nous souhaitons répondre dans cette thèse est de savoir si les approches relationnelles et graphes sont incompatible, ou s’il est possible de les combiner de manière avantageuse. En particulier, il serait souhaitable de pouvoir conserver la performance des approches graphe, et la généralité des approches relationnelles. Dans ce cadre, nous réalisons un index structurel adapté aux données relationnelles. <p><p>Nous nous basons sur une méthodologie décrite par Fletcher et ses coauteurs pour la conception d’index structurels. Cette méthodologie repose sur trois composants principaux. Un premier composant est une caractérisation dite structurelle du langage de requêtes à supporter. Il s’agit ici de pouvoir identifier les données qui sont retournées en même temps par n’importe quelle requête du langage aussi précisément que possible. Un second composant est un algorithme qui doit permettre de grouper efficacement les données qui sont retournées en même temps, d’après la caractérisation structurelle. Le troisième composant est l’index en tant que tel. Il s’agit d’une structure de données qui doit permettre d’identifier les groupes de données, générés par l’algorithme précédent pour répondre aux requêtes. <p><p>Dans un premier temps, il faut remarquer que le langage SPARQL pris dans sa totalité ne se prête pas à la réalisation d’index structurels efficaces. En effet, le fondement des requêtes SPARQL se situe dans l’expression de requêtes conjonctives. La caractérisation structurelle des requêtes conjonctives est connue, mais ne se prête pas à la construction d’algorithmes efficaces pour le groupement. Néanmoins, l’étude empirique des requêtes SPARQL posées en pratique que nous réalisons au Chapitre 5 montre que celles-ci sont principalement des requêtes conjonctives acycliques. Les requêtes conjonctives acycliques sont connues dans la littérature pour admettre des algorithmes d’évaluation efficaces. <p><p>Le premier composant de notre index structurel, introduit au Chapitre<p>6, est une caractérisation des requêtes conjonctives acycliques. Cette<p>caractérisation est faite en termes de guarded simulation. Pour les graphes la<p>notion de simulation est une version restreinte de la notion de bisimulation.<p>Similairement, nous introduisons la notion de guarded simulation comme une<p>restriction de la notion de guarded bisimulation, une extension connue de la<p>notion de bisimulation aux données relationelles. <p><p>Le Chapitre 7 offre un second composant de notre index structurel. Ce composant est une structure de données appelée guarded structural index qui supporte le traitement de requêtes conjonctives quelconques. Nous montrons que, couplé à la caractérisation structurelle précédente, cet index permet d’identifier de manière optimale les données utiles au traitement de requêtes conjonctives acycliques. <p><p>Le Chapitre 8 constitue le troisième composant de notre index structurel et propose des méthodes efficaces pour calculer la notion de guarded simulation. Notre algorithme consiste essentiellement en une transformation d’une base de données en un graphe particulier, sur lequel les notions de simulation et guarded simulation correspondent. Il devient alors possible de réutiliser les algorithmes existants pour calculer des relations de simulation. <p><p>Si les chapitres précédents définissent une base nécessaire pour un index structurel visant les données relationnelles, ils n’intègrent pas encore cet index dans le contexte d’un moteur de bases de données relationnelles. C’est ce que propose le Chapitre 9, en développant des méthodes qui permettent de prendre en compte l’index durant le traitement d’une requête SPARQL. Des résultats expérimentaux probants complètent cette étude. <p><p>Ce travail apporte donc une première réponse positive à la question de savoir s’il est possible de combiner de manière avantageuse les approches relationnelles et graphes de stockage de données RDF.<p><br>Doctorat en Sciences de l'ingénieur<br>info:eu-repo/semantics/nonPublished
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Liu, Jixue. "View maintenance in nested relations and object-relational databases." 2000. http://arrow.unisa.edu.au:8081/1959.8/24993.
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A materialized view is a derived data collecton stored in a database. When the source data for a materialized view is updated, the materialized view also needs to be updated. The process of updating a materialized view in response to changes in the source data is called view maintenance. There are two methods for maintaining a materialized view - recomputation and incremental computation. Recomputation computes the new view instance from scratch using the updated sources data. Incremental computation on the other hand, computes the new view instance by using the update to the source data, the old view instance, and possibly some source data. Incremental computation is widely accepted as a less expensive mathod of maintaining a view when the size of the update to the source data is small in relation to the size of the source data.<br>thesis (PhD)--University of South Australia, 2000
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Fonseca, Guilherme António Duarte. "On Forgetting Relations in Relational Databases." Master's thesis, 2022. http://hdl.handle.net/10362/135417.
Full textAbstract:
Although not usually acknowledged as such, forgetting is a crucial aspect of human reasoning.
It allows us to deal with large amounts of information, pushing irrelevant details
out of our consciousness so that we can focus on the essential knowledge. Motivated
by its beneficial effect on the human brain, this operation has been emulated in many
formalisms in the field of Knowledge Representation and Reasoning, where several approaches
to forgetting have been proposed. In common, these support computer systems
dealing with inaccurate or excessive information without negatively affecting the remaining
knowledge. More recently, the General Data Protection Regulation’s ‘right to be
forgotten’ has given additional impetus to the study of this operation.
Surprisingly, forgetting has not yet been studied in relational databases, the most
widespread technology for knowledge representation. This is a serious drawback that
needs to be addressed, considering the prominence of databases in our society and the
relevance of the operation in numerous knowledge processing tasks.
In this dissertation, we take the first steps to tackle this need, proposing a theoretical
investigation of forgetting relations in relational databases. We start by introducing
an alternative formalisation of the relational model, which includes a novel notion of
equivalence between databases. Afterwards, we look further into the problem of forgetting.
We formally define the general concept of a relation forgetting operator and present
concrete operators, each aligned with a distinct view on the operation and thus with its
unique features. Moreover, we illustrate the operators with examples inspired by realistic
situations. Finally, we evaluate them. For that, we formalise in the form of properties
the requirements that guided the definition of the operators and prove that they satisfy
desirable properties. Ultimately, with this work, we motivate the importance of forgetting
in relational databases and lay the foundations for its study.<br>Embora nem sempre reconhecido como tal, o esquecimento é um aspeto crucial do raciocínio
humano, pois permite-nos lidar com grandes quantidades de informação, ajudandonos
a concentrar no conhecimento essencial. Motivada pelo seu efeito benéfico no cérebro
humano, esta operação tem sido emulada em diversos formalismos na área da Representação
do Conhecimento e Raciocínio, onde várias abordagens ao esquecimento têm sido
propostas. Em comum, estas apoiam sistemas informáticos a lidar com informação imprecisa
ou excessiva sem afetar negativamente o restante conhecimento. Mais recentemente,
o ‘direito ao esquecimento’ do Regulamento Geral sobre a Proteção de Dados deu um
impulso extra ao estudo desta operação.
Surpreendentemente, o esquecimento ainda não foi estudado em bases de dados relacionais,
a tecnologia mais utilizada para representação de conhecimento. Este é um
grave inconveniente a resolver, tendo em conta a proeminência das bases de dados na
nossa sociedade e a relevância da operação em inúmeras tarefas de processamento de
conhecimento.
Nesta dissertação, damos os primeiros passos no sentido de fazer frente a esta necessidade,
propondo uma investigação teórica do esquecimento de relações em bases de
dados relacionais. Começamos por introduzir uma formalização alternativa do modelo
relacional, que inclui uma nova noção de equivalência entre bases de dados. Posteriormente,
analisamos mais aprofundadamente o problema do esquecimento. Definimos
formalmente o conceito geral de um operador de esquecimento de relações e apresentamos
operadores concretos, cada um alinhado com uma visão distinta sobre a operação
e, portanto, com as suas características únicas. Ademais, ilustramos os operadores com
exemplos inspirados em situações reais. Finalmente, avaliamo-los. Para isso, formalizamos
sob a forma de propriedades os requisitos que orientaram a definição dos operadores
e provamos que estes satisfazem propriedades desejáveis. Em última análise, com este
trabalho, motivamos a importância do esquecimento em bases de dados relacionais e
estabelecemos as bases para o seu estudo.
50
Chang, Wei-Yi, and 張葦怡. "Fuzzy Relational Databases." Thesis, 2004. http://ndltd.ncl.edu.tw/handle/42005297366678074217.
Full textAbstract:
碩士<br>元智大學<br>資訊管理研究所<br>92<br>This research discuss about the topic of such application type as fuzzy relation database, fuzzy function dependence, fuzzy multiple-value dependence, and introduction of four kinds of the fuzzy relation database. During the process of database designing, the normalization is getting become as a very important problem on fuzzy relation database. The function of normalization in database can be evaded the happening of distortion and data reoccurrence; data dependence during the normalization with regarding to function dependence, multiple-value function dependence can also thought of as an importance issue.
Fuzzy function dependence, fuzzy multiple-value dependence is refers to the relationship of attributes, whether attribute of all non-primary key depends upon the primary key in the relation table. Besides, there are many kind of fuzzy data expression methods, therefore, whether to compare the value of two tuple attributes with each other is equal or not, should have tested through the measurement of such semantic relation among the attributes of fuzzy data. Suppose to compare results of such measuring with each other is equal to the degree of semantic, the more approaching to the value of 1; the more equality of such fuzzy data.