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Data model

About: Data model is a research topic. Over the lifetime, 12734 publications have been published within this topic receiving 251640 citations. The topic is also known as: datamodel & data models.


Papers
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Book
17 Oct 2013
TL;DR: A data model, called the entity-relationship model, is proposed that incorporates some of the important semantic information about the real world and can be used as a basis for unification of different views of data: the network model, the relational model, and the entity set model.
Abstract: A data model, called the entity-relationship model, is proposed. This model incorporates some of the important semantic information in the real world. A special diagramatic technique is introduced as a tool for data base design. An example of data base design and description using the model and the diagramatic technique is given. Some implications on data integrity, information retrieval, and data manipulation are discussed.The entity-relationship model can be used as a basis for unification of different views of data: the network model, the relational model, and the entity set model. Semantic ambiguities in these models are analyzed. Possible ways to derive their views of data from the entity-relationship model are presented.

5,941 citations

Proceedings ArticleDOI
22 Sep 1975
TL;DR: A data model, called the entity-relationship model, which incorporates the semantic information in the real world is proposed, and a special diagramatic technique is introduced for exhibiting entities and relationships.
Abstract: A data model, called the entity-relationship model, is proposed. This model incorporates some of the important semantic information about the real world. A special diagrammatic technique is introduced as a tool for database design. An example of database design and description using the model and the diagrammatic technique is given. Some implications for data integrity, information retrieval, and data manipulation are discussed.The entity-relationship model can be used as a basis for unification of different views of data: the network model, the relational model, and the entity set model. Semantic ambiguities in these models are analyzed. Possible ways to derive their views of data from the entity-relationship model are presented.

3,693 citations

Journal Article
TL;DR: A model based on n-ary relations, a normal form for data base relations, and the concept of a universal data sublanguage are introduced and certain operations on relations are discussed and applied to the problems of redundancy and consistency in the user's model.

3,311 citations

Book
01 Sep 1997
TL;DR: Fuzzy Databases: Principles and Applications is comprehensive covering all of the major approaches and models of fuzzy databases that have been developed including coverage of commercial/industrial systems and applications.
Abstract: From the Publisher: This volume presents the results of approximately 15 years of work from researchers around the world on the use of fuzzy set theory to represent imprecision in databases. The maturity of the research in the discipline and the recent developments in commercial/industrial fuzzy databases provided an opportunity to produce this survey. Fuzzy Databases: Principles and Applications is self-contained providing background material on fuzzy sets and database theory. It is comprehensive covering all of the major approaches and models of fuzzy databases that have been developed including coverage of commercial/industrial systems and applications. Background and introductory material are provided in the first two chapters. The major approaches in fuzzy databases comprise the second part of the volume. This includes the use of similarity and proximity measures as the fuzzy techniques used to extend the relational data modeling and the use of possibility theory approaches in the relational model. Coverage includes extensions to the data model, querying approaches, functional dependencies and other topics including implementation issues, information measures, database security, alternative fuzzy data models, the IFO model, and the network data models. A number of object-oriented extensions are also discussed. The use of fuzzy data modeling in geographical information systems (GIS) and use of rough sets in rough and fuzzy rough relational data models are presented. Major emphasis has been given to applications and commercialization of fuzzy databases. Several specific industrial/commercial products and applications are described. These include approaches to developing fuzzy front-end systems and special-purpose systems incorporating fuzziness.

3,239 citations

Book
01 Jul 1983
TL;DR: This book will not become a unity of the way for you to get amazing benefits at all, but, it will serve something that will let you get the best time and moment to spend for reading the book.
Abstract: It sounds good when knowing the conceptual structures information processing in mind and machine in this website. This is one of the books that many people looking for. In the past, many people ask about this book as their favourite book to read and collect. And now, we present hat you need quickly. It seems to be so happy to offer you this famous book. It will not become a unity of the way for you to get amazing benefits at all. But, it will serve something that will let you get the best time and moment to spend for reading the book.

3,204 citations


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
20226
2021345
2020491
2019633
2018645
2017574