Relevant bibliographies by topics / Database management. Querying (Computer science)

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Database management. Querying (Computer science)'

Author: Grafiati
Published: 4 June 2021
Last updated: 4 February 2022

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Journal articles on the topic "Database management. Querying (Computer science)"

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Buneman, O. P., S. B. Davidson, and A. Watters. "Querying independent databases." Information Sciences 52, no. 1 (October 1990): 1–34. http://dx.doi.org/10.1016/0020-0255(90)90033-7.

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Bouaziz, Rafik, Salem Chakhar, Vincent Mousseau, Sudha Ram, and Abdelkader Telmoudi. "Database design and querying within the fuzzy semantic model." Information Sciences 177, no. 21 (November 2007): 4598–620. http://dx.doi.org/10.1016/j.ins.2007.05.013.

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Kacprzyk, Janusz, and Sławomir Zadrożny. "Computing with words in intelligent database querying: standalone and Internet-based applications." Information Sciences 134, no. 1-4 (May 2001): 71–109. http://dx.doi.org/10.1016/s0020-0255(01)00093-7.

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Koprulu, Mesru, Nihan Kesim Cicekli, and Adnan Yazici. "Spatio-temporal querying in video databases." Information Sciences 160, no. 1-4 (March 2004): 131–52. http://dx.doi.org/10.1016/j.ins.2003.08.011.

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Erozel, Guzen, Nihan Kesim Cicekli, and Ilyas Cicekli. "Natural language querying for video databases." Information Sciences 178, no. 12 (June 2008): 2534–52. http://dx.doi.org/10.1016/j.ins.2008.02.001.

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Sözer, Aziz, Adnan Yazıcı, Halit Oğuztüzün, and Osman Taş. "Modeling and querying fuzzy spatiotemporal databases." Information Sciences 178, no. 19 (October 2008): 3665–82. http://dx.doi.org/10.1016/j.ins.2008.05.034.

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Yarygina, Anna, and Boris Novikov. "Optimizing resource allocation for approximate real-time query processing." Computer Science and Information Systems 11, no. 1 (2014): 69–88. http://dx.doi.org/10.2298/csis120825063y.

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Query optimization techniques are proved to be essential for high performance of database management systems. In the context of new querying paradigms, such as similarity based search, exact query evaluation is neither computationally feasible nor meaningful, and approximate query evaluation is the only reasonable option. In this paper a problem of resource allocation for approximate evaluation of complex queries is considered. An approximate algorithm for a near-optimal resource allocation is presented, providing the best feasible quality of the output subject to a limited total cost of a query. The results of experiments have shown that the approximate resource allocation algorithm is accurate and efficient.
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Xue, Qiang, Sakti Pramanik, Gang Qiang, and Qiang Zhu. "A hybrid index structure for querying large string databases." International Journal of Electronic Business 3, no. 3/4 (2005): 243. http://dx.doi.org/10.1504/ijeb.2005.007269.

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Gammoudi, Aymen, Allel Hadjali, and Boutheina Ben Yaghlane. "Fuzz-TIME: an intelligent system for managing fuzzy temporal information." International Journal of Intelligent Computing and Cybernetics 10, no. 2 (June 12, 2017): 200–222. http://dx.doi.org/10.1108/ijicc-09-2016-0036.

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Purpose Time modeling is a crucial feature in many application domains. However, temporal information often is not crisp, but is subjective and fuzzy. The purpose of this paper is to address the issue related to the modeling and handling of imperfection inherent to both temporal relations and intervals. Design/methodology/approach On the one hand, fuzzy extensions of Allen temporal relations are investigated and, on the other hand, extended temporal relations to define the positions of two fuzzy time intervals are introduced. Then, a database system, called Fuzzy Temporal Information Management and Exploitation (Fuzz-TIME), is developed for the purpose of processing fuzzy temporal queries. Findings To evaluate the proposal, the authors have implemented a Fuzz-TIME system and created a fuzzy historical database for the querying purpose. Some demonstrative scenarios from history domain are proposed and discussed. Research limitations/implications The authors have conducted some experiments on archaeological data to show the effectiveness of the Fuzz-TIME system. However, thorough experiments on large-scale databases are highly desirable to show the behavior of the tool with respect to the performance and time execution criteria. Practical implications The tool developed (Fuzz-TIME) can have many practical applications where time information has to be dealt with. In particular, in several real-world applications like history, medicine, criminal and financial domains, where time is often perceived or expressed in an imprecise/fuzzy manner. Social implications The social implications of this work can be expected, more particularly, in two domains: in the museum to manage, exploit and analysis the piece of information related to archives and historic data; and in the hospitals/medical organizations to deal with time information inherent to data about patients and diseases. Originality/value This paper presents the design and characterization of a novel and intelligent database system to process and manage the imperfection inherent to both temporal relations and intervals.
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Samson, Grace L., Joan Lu, and Aminat A. Showole. "Mining Complex Spatial Patterns: Issues and Techniques." Journal of Information & Knowledge Management 13, no. 02 (June 2014): 1450019. http://dx.doi.org/10.1142/s0219649214500191.

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Spatial data mining is the quantitative study of phenomena that are located in space. This paper investigates methods of mining patterns of a complex spatial data set (which generally describes any kind of data where the location in space of object holds importance). We based this research on the analysis of some spatial characteristics of certain objects. We began with describing the spatial pattern of events or objects with respect to their attributes; we looked at how to describe the spatial nature/characteristics of entities in an environment with respect to their spatial and non-spatial attributes. We also looked at modelling (predictive modelling/knowledge management of complex spatial systems), querying and implementing a complex spatial database (using data structure and algorithms). Critically speaking, the presence of spatial auto-correlation and the fact that continuous data types are always present in spatial data makes it important to create methods, tools and algorithms to mine spatial patterns in a complex spatial data set. This work is particularly useful to researchers in the field of data mining as it contributes a whole lot of knowledge to different application areas of data mining especially spatial data mining. It can also be useful in teaching and likewise for other study purposes.
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Dissertations / Theses on the topic "Database management. Querying (Computer science)"

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Thiagarajan, Arvind. "Representing and querying regression models in a relational database management system." Thesis, Massachusetts Institute of Technology, 2007. http://hdl.handle.net/1721.1/42254.

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Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2007.
Includes bibliographical references (p. 77-79).
Curve fitting is a widely employed, useful modeling tool in several financial, scientific, engineering and data mining applications, and in applications like sensor networks that need to tolerate missing or noisy data. These applications need to both fit functions to their data using regression, and pose relational-style queries over regression models. Unfortunately, existing DBMSs are ill suited for this task because they do not include support for creating, representing and querying functional data, short of brute-force discretization of functions into a collection of tuples. This thesis describes FunctionDB, a novel DBMS that extends the state of the art. FunctionDB treats functions output by regression as first-class citizens that can be queried declaratively and manipulated like traditional database relations. The key contributions of FunctionDB are a compact, algebraic representation for regression models as piecewise functions, and an algebraic query processor that executes declarative queries directly on this representation as combinations of algebraic operations like function inversion, zero finding and symbolic integration. FunctionDB is evaluated on two real world data sets: measurements from a temperature sensor network, and traffic traces from cars driving on Boston roads. The results show that operating in the functional domain has substantial accuracy advantages (over 15% for some queries) and order of magnitude (10x-100x) performance gains over existing approaches that represent models as discrete collections of points. The thesis also describes an algorithm to maintain regression models online, as new raw data is inserted into the system. The algorithm supports a sustained insertion rate of the order of a million records per second, while generating models no less compact than a clairvoyant (offline) strategy.
by Arvind Thiagarajan.
S.M.
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Kwan, Kang-lun. "Adaptive stream filters for entity-based queries with non-value tolerance." Click to view the E-thesis via HKUTO, 2007. http://sunzi.lib.hku.hk/hkuto/record/B3884333X.

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Kwan, Kang-lun, and 關庚麟. "Adaptive stream filters for entity-based queries with non-value tolerance." Thesis, The University of Hong Kong (Pokfulam, Hong Kong), 2007. http://hub.hku.hk/bib/B3884333X.

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Acar, Aybar C. "Query consolidation interpreting queries sent to independent heterogenous databases /." Fairfax, VA : George Mason University, 2008. http://hdl.handle.net/1920/3223.

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Thesis (Ph.D.)--George Mason University, 2008.
Vita: p. 169. Thesis director: Amihai Motro. Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in Computer Science. Title from PDF t.p. (viewed Aug. 27, 2008). Includes bibliographical references (p. 162-168). Also issued in print.
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Fernández, Moctezuma Rafael J. "A Data-Descriptive Feedback Framework for Data Stream Management Systems." PDXScholar, 2012. https://pdxscholar.library.pdx.edu/open_access_etds/116.

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Data Stream Management Systems (DSMSs) provide support for continuous query evaluation over data streams. Data streams provide processing challenges due to their unbounded nature and varying characteristics, such as rate and density fluctuations. DSMSs need to adapt stream processing to these changes within certain constraints, such as available computational resources and minimum latency requirements in producing results. The proposed research develops an inter-operator feedback framework, where opportunities for run-time adaptation of stream processing are expressed in terms of descriptions of substreams and actions applicable to the substreams, called feedback punctuations. Both the discovery of adaptation opportunities and the exploitation of these opportunities are performed in the query operators. DSMSs are also concerned with state management, in particular, state derived from tuple processing. The proposed research also introduces the Contracts Framework, which provides execution guarantees about state purging in continuous query evaluation for systems with and without inter-operator feedback. This research provides both theoretical and design contributions. The research also includes an implementation and evaluation of the feedback techniques in the NiagaraST DSMS, and a reference implementation of the Contracts Framework.
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Elliott, Brendan David. "Hierarchical and Semantic Data Management and Querying for Patient Records and Personal Photos." Case Western Reserve University School of Graduate Studies / OhioLINK, 2009. http://rave.ohiolink.edu/etdc/view?acc_num=case1226303040.

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Hossain, Md Delwar. "Querying communities of interest in peer database networks." Thesis, University of Ottawa (Canada), 2005. http://hdl.handle.net/10393/26926.

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Peer-to-Peer (P2P) networks are used primarily for file sharing. P2P user communities are continuing to grow rapidly, but there is no specific query mechanism for communities of interest in peer database networks. Peer databases are linked to each other through acquaintances. These are individual, independently developed databases that contain local data. Many researchers have tackled the problem of query processing in P2P networks. Moreover, researchers have started to investigate community-based querying in peer database networks. The focus of this thesis is to study a query translation mechanism, to develop an algorithm for querying communities of interest in peer database networks, and to implement a prototype of this algorithm. P2P communities are formed using common claimed items. First, we investigate an existing community formation and discovery algorithm for a text file, as well as an existing query translation mechanism for peer databases. After that, we develop a community-based search algorithm for peer databases. The developed algorithm combines the aforementioned community formation and discovery with the query translation mechanisms. A prototype has been developed and experimental results are shown. An approach for discovering communities 'on the fly' is introduced and a method for optimizing the community discovery technique is shown.
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Wang, Song. "State-Slice: A New Stream Query Optimization Paradigm for Multi-query and Distributed Processing." Worcester, Mass. : Worcester Polytechnic Institute, 2008. http://www.wpi.edu/Pubs/ETD/Available/etd-032508-044505/.

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Bandyopadhyay, Bortik. "Querying Structured Data via Informative Representations." The Ohio State University, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=osu1595447189545086.

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Papadopoulos, Stavros. "Authenticated query processing /." View abstract or full-text, 2010. http://library.ust.hk/cgi/db/thesis.pl?CSED%202010%20PAPADO.

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Books on the topic "Database management. Querying (Computer science)"

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Database repairing and consistent query answering. San Rafael, Calif. (1537 Fourth Street, San Rafael, CA 94901 USA): Morgan & Claypool, 2011.

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Weiyi, Meng, ed. Principles of database query processing for advanced applications. San Francisco, Calif: Morgan Kaufmann, 1998.

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Curé, Olivier. RDF database systems: Triples storage and SPARQL query processing. Amsterdam: Morgan Kaufmann, 2015.

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International Conference on Entity-Relationship Approach (8th 1989 Toronto, Ont.). Entity-relationship approach to database design and querying: Proceedings of the Eighth International Conference on Entity-Relationship Approach, Toronto, Canada, 18-20 October 1989. Amsterdam: North-Holland, 1990.

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Fritchey, Grant. SQL Server 2012 Query Performance Tuning. Berkeley, CA: Apress, 2012.

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Yan, Li. Handbook of research on innovative database query processing techniques. Hershey, PA: Information Science Reference, 2016.

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Ma, Zongmin, and Li Yan. Advanced database query systems: Techniques, applications and technologies. Edited by IGI Global. Hershey, Pa: IGI Global (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA), 2011.

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Salander, Elisabeth C., and Elisabeth C. Salander. Computer search algorithms. Hauppauge, N.Y: Nova Science Publishers, 2010.

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Salander, Elisabeth C. Computer search algorithms. Hauppauge, N.Y: Nova Science Publishers, 2010.

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Database machines and database management. Englewood Cliffs: Prentice-Hall, 1986.

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Book chapters on the topic "Database management. Querying (Computer science)"

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Bosc, Patrick, Ludovic Lietard, and Olivier Pivert. "Soft querying, a new feature for database management systems." In Lecture Notes in Computer Science, 631–40. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58435-8_229.

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Trißl, Silke, and Ulf Leser. "Querying Ontologies in Relational Database Systems." In Lecture Notes in Computer Science, 63–79. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11530084_7.

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Angles, Renzo, and Claudio Gutierrez. "Querying RDF Data from a Graph Database Perspective." In Lecture Notes in Computer Science, 346–60. Berlin, Heidelberg: Springer Berlin Heidelberg, 2005. http://dx.doi.org/10.1007/11431053_24.

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Weik, Martin H. "database management system." In Computer Science and Communications Dictionary, 340. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_4194.

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Grillmeyer, Oliver. "Database Management Systems." In Exploring Computer Science with Scheme, 285–318. New York, NY: Springer New York, 1998. http://dx.doi.org/10.1007/978-1-4757-2937-5_12.

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Pivert, Olivier, and Henri Prade. "Database Querying in the Presence of Suspect Values." In Communications in Computer and Information Science, 44–51. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-23201-0_6.

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Thalheim, Bernhard. "Visual SQL: Towards ER-Based Object-Relational Database Querying." In Lecture Notes in Computer Science, 520–21. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-87877-3_41.

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Li, Xiang, Ling Feng, and Lizhu Zhou. "Contextual Ranking of Database Querying Results: A Statistical Approach." In Lecture Notes in Computer Science, 126–39. Berlin, Heidelberg: Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-88793-5_10.

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Andreasen, Troels. "Flexible database querying based on associations of domain values." In Lecture Notes in Computer Science, 570–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 1997. http://dx.doi.org/10.1007/3-540-63614-5_55.

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Costa, Flavio, Vítor Silva, Daniel de Oliveira, Kary A. C. S. Ocaña, and Marta Mattoso. "Towards Supporting Provenance Gathering and Querying in Different Database Approaches." In Lecture Notes in Computer Science, 254–57. Cham: Springer International Publishing, 2015. http://dx.doi.org/10.1007/978-3-319-16462-5_26.

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Conference papers on the topic "Database management. Querying (Computer science)"

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Wang, Jinpeng, Zhuang Miao, Yafei Zhang, and Bo Zhou. "Querying Heterogeneous Relational Database using SPARQL." In 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science. IEEE, 2009. http://dx.doi.org/10.1109/icis.2009.11.

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Spahiu, Cosmin. "A multimedia database server for information storage and querying." In 2009 International Multiconference on Computer Science and Information Technology (IMCSIT). IEEE, 2009. http://dx.doi.org/10.1109/imcsit.2009.5352790.

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"The Management TQF Database Systems." In 2016 the 6th International Workshop on Computer Science and Engineering. WCSE, 2016. http://dx.doi.org/10.18178/wcse.2016.06.093.

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Raza, Basit, Abdul Mateen, Tauqeer Hussain, and M. M. Awais. "Autonomic Success in Database Management Systems." In 2009 Eighth IEEE/ACIS International Conference on Computer and Information Science. IEEE, 2009. http://dx.doi.org/10.1109/icis.2009.202.

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Xiong, Ruiying, Jinya Xu, and Yanran Huang. "Design and Implementation of Microblog Database Based on NoSQL and Relational Database." In 8th International Conference on Management and Computer Science (ICMCS 2018). Paris, France: Atlantis Press, 2018. http://dx.doi.org/10.2991/icmcs-18.2018.90.

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"On the Application of Computer Database System In Information Management." In 2020 Conference on Educational Science and Educational Skills. Scholar Publishing Group, 2020. http://dx.doi.org/10.38007/proceedings.0000595.

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Jung, Ji Won, Seung Kwon Jung, Jin Tak Choi, and Dong Seop Lee. "A study on Standardization of Integrated database for Intelligent water information management." In Information Technology and Computer Science 2015. Science & Engineering Research Support soCiety, 2015. http://dx.doi.org/10.14257/astl.2015.99.33.

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Kong, Myeongsik, Hyundong Lee, Hongcheol Shin, and Miyun Park. "Study on Inventory Database Construction for Asset Management in Water Supply System." In Information Technology and Computer Science 2016. Science & Engineering Research Support soCiety, 2016. http://dx.doi.org/10.14257/astl.2016.136.17.

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Pan, Wu-min, and Shanshan Sun. "Study of data mapping for RDBMS (relational database management system) data to NoSQL." In 2013 International Conference on Sport Science and Computer Science. Southampton, UK: WIT Press, 2014. http://dx.doi.org/10.2495/cccs130471.

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Qian Tonghui, Qi Yang, Cai Limin, Shi Zili, Cui Xiaowu, and Li Dehua. "The design of embedded database management system for mobile computing." In 2012 International Conference on Computer Science and Information Processing (CSIP). IEEE, 2012. http://dx.doi.org/10.1109/csip.2012.6309139.

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