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Relevant bibliographies by topics / Entity relationship model

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Academic literature on the topic 'Entity relationship model'

Author: Grafiati

Published: 4 June 2021

Last updated: 11 February 2022

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Journal articles on the topic "Entity relationship model"

1

Lee, Heon-Ki. "Semantics of recursive relationships in entity-relationship model." Information and Software Technology 41, no. 13 (September 1999): 877–86. http://dx.doi.org/10.1016/s0950-5849(99)00045-2.

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Buff, H. W. "The rational model contra entity relationship?" ACM SIGMOD Record 21, no. 3 (September 1992): 33–34. http://dx.doi.org/10.1145/140979.140995.

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González Jiménez, Luis. "REERM: Reenhancing the entity–relationship model." Data & Knowledge Engineering 58, no. 3 (September 2006): 410–35. http://dx.doi.org/10.1016/j.datak.2005.05.004.

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Tokola, T., A. Turkia, J. Sarkeala, and J. Soimasuo. "An entity-relationship model for forest inventory." Canadian Journal of Forest Research 27, no. 10 (October 1, 1997): 1586–94. http://dx.doi.org/10.1139/x97-127.

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Saiedian, Hossein. "An evaluation of extended entity-relationship model." Information and Software Technology 39, no. 7 (January 1997): 449–62. http://dx.doi.org/10.1016/s0950-5849(97)00002-5.

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Gorman, Kevin, and Joobin Choobineh. "The Object-Oriented Entity-Relationship Model (Ooerm)." Journal of Management Information Systems 7, no. 3 (December 1990): 41–65. http://dx.doi.org/10.1080/07421222.1990.11517896.

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Wojda, Piotr, Serge Brouyère, Johan Derouane, and Alain Dassargues. "HydroCube: an entity-relationship hydrogeological data model." Hydrogeology Journal 18, no. 8 (October 15, 2010): 1953–62. http://dx.doi.org/10.1007/s10040-010-0653-6.

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Blanning, Robert W. "An entity-relationship approach to model management." Decision Support Systems 2, no. 1 (March 1986): 65–72. http://dx.doi.org/10.1016/0167-9236(86)90122-3.

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Lee, Edward T., P. Chu, and C. Peng Wu. "Applications of entity-relationship model to picture description." Robotica 5, no. 3 (July 1987): 231–34. http://dx.doi.org/10.1017/s0263574700015885.

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SUMMARYThe concepts of entity-relationship diagram have been applied to picture description. Primitive picture entities, picture relationships, and picture grammars are presented with illustrative examples. A high-level description of a two-level picture generation system is proposed using either string description or ER diagram description. Illustrative examples are also given. The advantages of ER diagram description together with its comparison to string description are also presented. The results may have useful applications in robotics, artificial intelligence, expert systems, picture processing, pattern recognition, knowledge engineering and pictorial database design.

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Wang, Litao, Meisheng Jia, Cheng Peng, Shunjiang Ni, and Shifei Shen. "Scenario-Entity Analysis based on an entity-relationship model: Revisiting crime reconstruction." Forensic Science International 302 (September 2019): 109923. http://dx.doi.org/10.1016/j.forsciint.2019.109923.

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Dissertations / Theses on the topic "Entity relationship model"

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Hassan, Mansoor Ahmed. "View integration using the entity-relationship model." Thesis, Aston University, 1989. http://publications.aston.ac.uk/10641/.

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Chan, Hock Chuan. "A knowledge level user interface using the entity-relationship model." Thesis, University of British Columbia, 1989. http://hdl.handle.net/2429/29070.

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The relational database system has achieved widespread popularity; however, it is still very difficult for users, even those trained in the relational model, to formulate relational queries. The major cause of the difficulties is the fact that the user and the database system communicate using constructs that are not closely related to the user's world. This dissertation develops a new level of user-database interaction — the knowledge level (KL) interface — where the user and the database system exchange only knowledge of the domain. The data structure used in the database is fully hidden from the user. In this way, the query is very closely related to the user's world. Under the new KL approach, the database system is no longer seen as a store of data. It is set up as an agent to know the domain knowledge told to it by the user. The system will then provide the knowledge required by the user during retrievals. It will use elements of the entity-relationship model for communicating knowledge about the real world with the user. It is shown that the KL interface is in many ways better than the relational interface. Users of the KL interface need to know less and perform fewer data manipulation operations than users of the relational interface. The KL interface also achieves both physical and logical data independence, unlike the relational system which does not truly achieve logical data independence. This dissertation also proposes a new approach to understanding the meaning of completeness of a query language, breaking away from the traditional calculus-based measure of completeness. This new approach is then applied to the development of the knowledge level interface. The main contributions of this dissertation are the proposal and development of a knowledge level interface, the anaylsis to show that this interface is better than the relational interface, and the demonstration that such an interface is feasible even for large databases.
Business, Sauder School of
Graduate

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Metz, Gale Lynn. "The units of measure consistency checker for the entity-relationship-attribute requirements model." Thesis, Kansas State University, 1986. http://hdl.handle.net/2097/9941.

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Lindsey, Daniel A. "A framework for classifying and resolving semantic conflicts using the enhanced entity-relationship model." Thesis, Monterey, California. Naval Postgraduate School, 1992. http://hdl.handle.net/10945/23683.

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Gažmerčík, Jakub. "Kompletný dátový model ITILu." Master's thesis, Vysoká škola ekonomická v Praze, 2011. http://www.nusl.cz/ntk/nusl-124731.

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The objective of this thesis is to design a complete ITIL (IT Infrastructure Library) data model by using Entity-Relationship diagram and the argumentation of this model in relation to ITIL Configuration and Asset Management federative approach. The thesis is build of two major parts, where the first one focuses on the theory of recommendations and best practices in the IT Governance processes, its relationship to ITIL and a high-level overview of ITIL history. Theoretical part ends with the brief description of tools and methods used in data modeling. It is followed by practical part in which the content is based on analyzing of ITIL publications in the same order as IT Service Management life cycle phases and designing of the logical data model. Each chapter discusses at its end the abiliity of designed model to cover the data requirements for particular ITSM lifecycle phase. In the very last chapter, all partial models are joined into one complete data model and shown relations are argumented.

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Watanabe, Toyohide, Yuusuke Uehara, Yuuji Yoshida, and Teruo Fukumura. "A semantic data model for intellectual database access." IEEE, 1990. http://hdl.handle.net/2237/6923.

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Lin, Chia-Yang. "Conceptual model builder." CSUSB ScholarWorks, 2004. https://scholarworks.lib.csusb.edu/etd-project/2708.

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Whenever one designs a new database system, an Entity-Relationship Diagram (ER diagram) is always needed to present the structure of this database. Using the graphically well-arranged ER Diagram helps you to easily understand the entities, attributes, domains, primary keys, foreign keys, constraints, and relationships inside a database. This data-modeling tool is an ideal choice for companies and developers.

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Parent, Christine. "L'approche erc : un modele de donnees et une algebre de type entite relation." Paris 6, 1987. http://www.theses.fr/1987PA066568.

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Presentation des definitions formelles d'un modele de donnees, d'une algebre associee et des proprietes mathematiques de ses operateurs. Le modele propose est le plus general possible par rapport aux possibilites liees aux trois concepts de base de l'approche entite relation (type d'entite, type de relation et attribut), avec notamment des attributs a structure recursive et des valeurs doubles

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SILBER-GUTH, CATHERINE. "Un cadre pour specifier une base d'objets complexes : application a la teledetection spatiale." Université Louis Pasteur (Strasbourg) (1971-2008), 1989. http://www.theses.fr/1989STR13022.

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Etude des problemes de specification de bases de donnees relationnelles. Il se resume en une demarche qui allie l'emploi du modele entite/association, d'un langage de types et de la methode deductive medee. Le travail a ete applique a la conception et realisation d'une base de donnees en teledetection, application qui s'est averee complexe car elle est confrontee a un volume colossal de donnees diverses

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Szakács, Tomáš. "Android aplikace pro doplňování zásob pojízdných kaváren." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2020. http://www.nusl.cz/ntk/nusl-417688.

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My diploma thesis is focused on a comprehensive analysis of a selected company, its business environment and possible risks associated with the implementation of the proposed change in the supply process using a mobile application. My proposed solution includes a risk reduction method, a complex view of the processes in the application and its graphic design, along with the estimated costs of implementing the change.

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Books on the topic "Entity relationship model"

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Gogolla, Martin, ed. An Extended Entity-Relationship Model. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-57648-7.

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Gogolla, Martin. An extended entity-relationship model: Fundamentals and pragmatics. Berlin: Springer-Verlag, 1994.

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An extended entity-relationship model: Fundamentals and pragmatics. Berlin: Springer-Verlag, 1994.

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Knight, D. R. Equivalence and transformation of entity-relationship type conceptual data models. Manchester: UMIST, 1995.

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Varlamov, Oleg. Mivar databases and rules. ru: INFRA-M Academic Publishing LLC., 2021. http://dx.doi.org/10.12737/1508665.

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The multidimensional open epistemological active network MOGAN is the basis for the transition to a qualitatively new level of creating logical artificial intelligence. Mivar databases and rules became the foundation for the creation of MOGAN. The results of the analysis and generalization of data representation structures of various data models are presented: from relational to "Entity — Relationship" (ER-model). On the basis of this generalization, a new model of data and rules is created: the mivar information space "Thing-Property-Relation". The logic-computational processing of data in this new model of data and rules is shown, which has linear computational complexity relative to the number of rules. MOGAN is a development of Rule - Based Systems and allows you to quickly and easily design algorithms and work with logical reasoning in the "If..., Then..." format. An example of creating a mivar expert system for solving problems in the model area "Geometry"is given. Mivar databases and rules can be used to model cause-and-effect relationships in different subject areas and to create knowledge bases of new-generation applied artificial intelligence systems and real-time mivar expert systems with the transition to"Big Knowledge". The textbook in the field of training "Computer Science and Computer Engineering" is intended for students, bachelors, undergraduates, postgraduates studying artificial intelligence methods used in information processing and management systems, as well as for users and specialists who create mivar knowledge models, expert systems, automated control systems and decision support systems. Keywords: cybernetics, artificial intelligence, mivar, mivar networks, databases, data models, expert system, intelligent systems, multidimensional open epistemological active network, MOGAN, MIPRA, KESMI, Wi!Mi, Razumator, knowledge bases, knowledge graphs, knowledge networks, Big knowledge, products, logical inference, decision support systems, decision-making systems, autonomous robots, recommendation systems, universal knowledge tools, expert system designers, logical artificial intelligence.

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International Conference on Entity-Relationship Approach (12th 1993 Arlington, Tex.). Entity-relationship approach, ER '93: 12th International Conference on the Entity-Relationship Approach, Arlington, Texas, USA, December 15-17, 1993 : proceedings. Berlin: Springer-Verlag, 1994.

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7

Handgraaf, Darrel L. Entity-Relationship Model vs. Extended Semantic Hierarchal model for conceptual modeling. 1986.

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Theodossakis, Emmanuel G. Specification of conceptual database schema languages: ---based on an extended entity-relationship model. Bradford, 1988.

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9

J, Holley P., and Leicester Polytechnic. Centre for Applied Research in Information Systems., eds. A Practical syntax checker for entity-relationship models. Leicester: The Polytechnic, 1987.

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(Editor), Ramez A. Elmasri, Vram Kouramajian (Editor), and Bernhard Thalheim (Editor), eds. Entity-Relationship Approach - ER '93: 12th International Conference on the Entity-Relationship Approach, Arlington, Texas, USA, December 15 - 17, 1993. Proceedings (Lecture Notes in Computer Science). Springer, 1994.

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Book chapters on the topic "Entity relationship model"

1

Song, Il-Yeol, and Peter P. Chen. "Entity Relationship Model." In Encyclopedia of Database Systems, 1315–22. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_148.

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Song, Il-Yeol, and Peter P. Chen. "Entity Relationship Model." In Encyclopedia of Database Systems, 1003–9. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_148.

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Song, Il-Yeol, and Peter P. Chen. "Entity Relationship Model." In Encyclopedia of Database Systems, 1–7. New York, NY: Springer New York, 2015. http://dx.doi.org/10.1007/978-1-4899-7993-3_148-2.

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Thalheim, Bernhard. "The Entity-Relationship Model." In Entity-Relationship Modeling, 29–54. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04058-4_3.

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Thalheim, Bernhard. "Extending the Entity-Relationship Model." In Entity-Relationship Modeling, 55–104. Berlin, Heidelberg: Springer Berlin Heidelberg, 2000. http://dx.doi.org/10.1007/978-3-662-04058-4_4.

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Gandhi, Munish, Edward L. Robertson, and Dirk Gucht. "Leveled entity relationship model." In Entity-Relationship Approach — ER '94 Business Modelling and Re-Engineering, 420–36. Berlin, Heidelberg: Springer Berlin Heidelberg, 1994. http://dx.doi.org/10.1007/3-540-58786-1_94.

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Levene, Mark, and George Loizou. "The Entity-Relationship Model." In A Guided Tour of Relational Databases and Beyond, 61–83. London: Springer London, 1999. http://dx.doi.org/10.1007/978-0-85729-349-7_2.

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Weik, Martin H. "entity-relationship data model." In Computer Science and Communications Dictionary, 526. Boston, MA: Springer US, 2000. http://dx.doi.org/10.1007/1-4020-0613-6_6286.

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Thalheim, Bernhard. "Extended Entity-Relationship Model." In Encyclopedia of Database Systems, 1417–26. New York, NY: Springer New York, 2018. http://dx.doi.org/10.1007/978-1-4614-8265-9_157.

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Thalheim, Bernhard. "Extended Entity-Relationship Model." In Encyclopedia of Database Systems, 1083–91. Boston, MA: Springer US, 2009. http://dx.doi.org/10.1007/978-0-387-39940-9_157.

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Conference papers on the topic "Entity relationship model"

1

Moss, Keith. "The Entity-Relationship model." In 2012 IEEE Global Engineering Education Conference (EDUCON). IEEE, 2012. http://dx.doi.org/10.1109/educon.2012.6201182.

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Roddick, J. F., and S. La-Ongsri. "Towards polymorphic relationships in the entity-relationship model." In International Conference on Computer Science and Systems Engineering. Southampton, UK: WIT Press, 2015. http://dx.doi.org/10.2495/csse140341.

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Shi, Minyong, Jingyi Huang, and Chunfang Li. "Entity Relationship Extraction Based on BLSTM Model." In 2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS). IEEE, 2019. http://dx.doi.org/10.1109/icis46139.2019.8940185.

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Cao, Fei, Barrett R. Bryant, Wei Zhao, Carol C. Burt, Rajeev R. Raje, Andrew M. Olson, and Mikhail Auguston. "Marshaling and unmarshaling models using the entity-relationship model." In the 2005 ACM symposium. New York, New York, USA: ACM Press, 2005. http://dx.doi.org/10.1145/1066677.1067025.

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Liquan Han, Jianchao Xu, and Qing'an Yao. "Entity-Relationship semantic meta-model based on ontology." In 2010 International Conference on Computer Application and System Modeling (ICCASM 2010). IEEE, 2010. http://dx.doi.org/10.1109/iccasm.2010.5623220.

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Lv, Jianghai, Junping Du, Nan Zhou, and Zhe Xue. "BERT-BIGRU-CRF: A Novel Entity Relationship Extraction Model." In 2020 IEEE International Conference on Knowledge Graph (ICKG). IEEE, 2020. http://dx.doi.org/10.1109/icbk50248.2020.00032.

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Yin, Dechun. "Chinese syntactic parsing based on linguistic entity-relationship model." In the 22nd ACM international conference. New York, New York, USA: ACM Press, 2013. http://dx.doi.org/10.1145/2505515.2507839.

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Spencer, H. J. "A mathematical schema for the entity-relationship data model." In the 1985 ACM annual conference. New York, New York, USA: ACM Press, 1985. http://dx.doi.org/10.1145/320435.320499.

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Czejdo, Bogdan, Ramez Elmasri, Marek Rusinkiewicz, and David W. Embley. "Semantics of update operations for an extended entity-relationship model." In the 1988 ACM sixteenth annual conference. New York, New York, USA: ACM Press, 1988. http://dx.doi.org/10.1145/322609.322632.

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Claverie, Steven D. "Operators in an extended entity-relationship model and their applications." In the 35th Annual Southeast Regional Conference. New York, New York, USA: ACM Press, 1997. http://dx.doi.org/10.1145/2817460.2817463.

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Reports on the topic "Entity relationship model"

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Yan, Yujie, and Jerome F. Hajjar. Automated Damage Assessment and Structural Modeling of Bridges with Visual Sensing Technology. Northeastern University, May 2021. http://dx.doi.org/10.17760/d20410114.

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Recent advances in visual sensing technology have gained much attention in the field of bridge inspection and management. Coupled with advanced robotic systems, state-of-the-art visual sensors can be used to obtain accurate documentation of bridges without the need for any special equipment or traffic closure. The captured visual sensor data can be post-processed to gather meaningful information for the bridge structures and hence to support bridge inspection and management. However, state-of-the-practice data postprocessing approaches require substantial manual operations, which can be time-consuming and expensive. The main objective of this study is to develop methods and algorithms to automate the post-processing of the visual sensor data towards the extraction of three main categories of information: 1) object information such as object identity, shapes, and spatial relationships - a novel heuristic-based method is proposed to automate the detection and recognition of main structural elements of steel girder bridges in both terrestrial and unmanned aerial vehicle (UAV)-based laser scanning data. Domain knowledge on the geometric and topological constraints of the structural elements is modeled and utilized as heuristics to guide the search as well as to reject erroneous detection results. 2) structural damage information, such as damage locations and quantities - to support the assessment of damage associated with small deformations, an advanced crack assessment method is proposed to enable automated detection and quantification of concrete cracks in critical structural elements based on UAV-based visual sensor data. In terms of damage associated with large deformations, based on the surface normal-based method proposed in Guldur et al. (2014), a new algorithm is developed to enhance the robustness of damage assessment for structural elements with curved surfaces. 3) three-dimensional volumetric models - the object information extracted from the laser scanning data is exploited to create a complete geometric representation for each structural element. In addition, mesh generation algorithms are developed to automatically convert the geometric representations into conformal all-hexahedron finite element meshes, which can be finally assembled to create a finite element model of the entire bridge. To validate the effectiveness of the developed methods and algorithms, several field data collections have been conducted to collect both the visual sensor data and the physical measurements from experimental specimens and in-service bridges. The data were collected using both terrestrial laser scanners combined with images, and laser scanners and cameras mounted to unmanned aerial vehicles.

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