Abstract
In recent years, a primary objective of the database community has been the incorporation of structured and complex data types. This has led to new database models based on both the established relational paradigm as well as the object-oriented paradigm. These new database models are the non-1NF relational data model (also called NF2 data model), object-oriented data model, and deductive object-oriented data model. These models are considered appropriate for modeling many non-traditional applications, such as CAD/CAM, imagery, multimedia, meteorology, geographic information systems, oceanography, etc. The NF2 data model is better suited for office automation systems. On the other hand, object-oriented databases are more appropriate for CAD/CAM, multimedia database and geographical, meteorological, and oceanographic applications. Object-oriented databases coupled with logic and as the more integrated approach, deductive object-oriented databases are more appropriate for knowledge intensive applications such as expert database systems. In this chapter, we introduce the logical database models such as the extended NF2 data model, the fuzzy object-oriented data model, and the fuzzy deductive object-oriented data model to deal with complex information and uncertainty that arise in non-conventional applications.
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Yazici, A., George, R. (1999). Logical Database Models for Uncertain Data. In: Fuzzy Database Modeling. Studies in Fuzziness and Soft Computing, vol 26. Physica, Heidelberg. https://doi.org/10.1007/978-3-7908-1880-2_4
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DOI: https://doi.org/10.1007/978-3-7908-1880-2_4
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