Semantic measure of fuzzy data in extended possibility-based fuzzy relational databases

An Extended Possibility-Based Fuzzy Nested Relational Database Model and Algebra

“…The corresponding attribute value, say ai, is a tuple of the form <ai 1, ai2, ... , aim> which is an element of Di 1 x Di2 x ... x Dirn (m> 1 and 1 :S; i:S; n), where each Dij (1 :S;j :S; m) may be a domain in (1), (2), (3), and (4) and even the set ofrelation values. Formally, the attribute domain of A (1 :S; i :S; n) is represented as follows.…”

“…The semantic relationships between two fuzzy data include equivalence, inclusion, intersection, and irrelevancy, which ean be assessed with semantic inclusion degree proposed in [2].…”

“…Based on similarity relation, a fuzzy NF 2 relational database model is introduced in [3] and two restructuring operations: Merge and Unmerge are emphatically given. In this paper, an extended possibility-based fuzzy NF 2 relational database model is introduced, where the fuzziness of data comes from possibility distributions over universes of discourse and as resemblance relation [2]. We give database model and define fuzzy nested algebra.…”

Consistent data operations for multi-databases in extended possibility-based data models

“…Different relation and different associated thresholds may either induce different equivalence classes, or yield different degree of closeness for a single pair of attribute values. Either equivalence classes (Buckles & Petry, 1982;Shenoi & Melton, 1989) or the closeness of attribute values (Chen et al, 1993;Chen, Vandenbulcke, & Kerre, 1992;Guu, Pang, & Liu, 2002;Ma, Zhang, & Ma, 2000;Rundensteiner, Hawkes, & Bandler, 1989) serves as the basis of data redundancy in various fuzzy database models (Buckles & Petry, 1982;Rundensteiner et al, 1989;Shenoi & Melton, 1989).…”

“…Under the consistency constraint, two different resemblance relations with appropriate threshold values for a domain can induce the same equivalence classes at any given level of cut. With the same equivalence classes, two fuzzy databases using the resemblance-based data model (Buckles & Petry, 1982;Shenoi & Melton, 1989) agree with each other in terms of data redundancy, also the databases using the extended possibility-based data model (Chen et al, 1993(Chen et al, , 1992Guu et al, 2002;Ma et al, 2000;Rundensteiner et al, 1989) exhibit the same closeness for the same pair of attribute values.…”