By Antonio Rosado, Rita A. Ribeiro, Slawomir Zadrozny, Janusz Kacprzyk (auth.), Gloria Bordogna Dr., Giuseppe Psaila Professor (eds.)
This quantity collects chosen contributions at the software of heterogeneous tools for coping with uncertainty and imprecision in databases. It includes either survey chapters on vintage subject matters similar to "flexible querying in databases", and recent ontributions
on "database types to symbolize imperfect data". Further, it comprises particular contributions on uncertainty administration in database integration, and in representing and
querying semistructured and spatial info. those themes are of specific relevance these days with the diffusion of the web considering the fact that, more often than not, functions require info unfold throughout numerous info resources and their integration may end up in inconsistent info. Semistructured details querying frequently demands the appliance of approximate matching recommendations, and spatial details is frequently incomplete and vague. analyzing this quantity can function a consultant to scholars for having a breathtaking view of the how to deal with uncertainty and imprecision in databases proposed up to now, to researchers to target the hottest learn developments, and to practitioners for having examples within which present databases include versatile functionalities for the administration of uncertainty and imprecision.
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Extra info for Flexible Databases Supporting Imprecision and Uncertainty
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Taxonomy G1. Possibilistic model G2. Similarity-based model G3. Hybrid models Proposals of FQLs for fuzzy databases P1. Prade and Testemale [34],[35] P2. Baldwin, Coyne and Martin [1] P3. Bosc and Pivert [8] P4. Buckles and Petry [12] P5. Buckles, Petry and Sachar [13] P6. Shenoi, Melton and Fan [42],[43] P7. Medina, Pons and Vila [32] P8. Galindo, Medina and Aranda [18] P9. Galindo, Medina, Pons and Cubero [20] Fig. 5. Taxonomy for Flexible Query Languages (FQLs) for fuzzy databases The proposed taxonomy includes three main groups.
The fuzzy operator proposed is defined as a combination of two operators. The first, denoted below with µ 'Pi , Flexible Query Languages for Relational Databases: an Overview 23 limits the contribution of condition Pj relatively to the contributions of all preceding conditions Pi (i The FDRC language is described next. ’s fuzzy domain calculus comprises the following atomic formulas [18]: 44 Antonio Rosado et al. H Name B Antonio Francisco Luis Address Reyes Católicos P. A. 8/30,1/ 31} Young Young [30,35] Juan Carlos Camino Ronda Julia Puerta Real Javier Gran Vía a) The generalized fuzzy relation Emp H Name Address B Antonio Reyes Católicos Francisco P. A. 6 (Emp). 5 S2 1 0 YOUNG MIDDLE OLD 16 25 30 35 40 45 50 55 c) Relation R: departments with at least one d) Labels definitions for attribute Age.