Matching strengths of answers in fuzzy relational databases

Imprecise information is represented by fuzzy disjunctive information, and an extended fuzzy relational model is used to accommodate such information. In the presence of imprecise information, answers to a query can be categorized into two kinds of answers: sure answers and possible answers. To find more likely answers to a given query, the authors develop a method to measure the matching strength of each tuple as an answer to the query. The quality of an answer is higher in the case where less extra information is required and the more sure information is provided.

[1]  Hans-Jürgen Zimmermann,et al.  Fuzzy Set Theory - and Its Applications , 1985 .

[2]  Adnan Yazici,et al.  Fuzzy information systems , 1992, [1992 Proceedings] IEEE International Conference on Fuzzy Systems.

[3]  L. Zadeh.  Fuzzy sets as a basis for a theory of possibility , 1999 .

[4]  Lotfi A. Zadeh,et al.  Fuzzy Sets , 1996, Inf. Control..

[5]  Bill P. Buckles,et al.  Information-theoretical characterization of fuzzy relational databases , 1983, IEEE Transactions on Systems, Man, and Cybernetics.

[6]  Arbee L. P. Chen,et al.  An Exploration of Relationships Among Exclusive Disjunctive Data , 1995, IEEE Trans. Knowl. Data Eng..

[7]  Settimo Termini,et al.  A Definition of a Nonprobabilistic Entropy in the Setting of Fuzzy Sets Theory , 1972, Inf. Control..

[8]  B. Buckles,et al.  A fuzzy representation of data for relational databases , 1982 .

[9]  Ding-An Chiang,et al.  Fuzzy information in extended fuzzy relational databases , 1997, Fuzzy Sets Syst..

[10]  R. Sunderraman,et al.  A Generalized Relational Model for Indefinite and Maybe Information , 1991, IEEE Trans. Knowl. Data Eng..

[11]  G. Klir,et al.  MEASURES OF UNCERTAINTY AND INFORMATION BASED ON POSSIBILITY DISTRIBUTIONS , 1982 .

[12]  Joan M. Morrissey,et al.  Imprecise information and uncertainty in information systems , 1990, TOIS.

[13]  Motohide Umano,et al.  FREEDOM-0: A FUZZY DATABASE SYSTEM , 1993 .

[14]  Raymond Reiter,et al.  Towards a Logical Reconstruction of Relational Database Theory , 1982, On Conceptual Modelling.

[15]  R. Yager.  ON THE MEASURE OF FUZZINESS AND NEGATION Part I: Membership in the Unit Interval , 1979 .

[16]  Frederick E. Petry,et al.  Extending the fuzzy database with fuzzy numbers , 1984, Inf. Sci..

[17]  Li-Yan Yuan,et al.  A sound and complete query evaluation algorithm for relational databases with disjunctive information , 1989, PODS '89.

[18]  Juan Miguel Medina,et al.  On the use of logical definition of fuzzy relational database , 1993, [Proceedings 1993] Second IEEE International Conference on Fuzzy Systems.

[19]  E. F. Codd,et al.  Extending the database relational model to capture more meaning , 1979, ACM Trans. Database Syst..

[20]  Witold Lipski,et al.  On semantic issues connected with incomplete information databases , 1979, ACM Trans. Database Syst..

[21]  Arun K. Majumdar,et al.  Fuzzy Functional Dependencies and Lossless Join Decomposition of Fuzzy Relational Database Systems , 1988, ACM Trans. Database Syst..

[22]  Sujeet Shenoi,et al.  An extended version of the fuzzy relational database model , 1990, Inf. Sci..

[23]  Arbee L. P. Chen,et al.  A Note on "Incomplete Relational Database Models Based on Intervals" , 1996, IEEE Trans. Knowl. Data Eng..

[24]  Henri Prade,et al.  Lipski's approach to incomplete information databases restated and generalized in the setting of Zadeh's possibility theory , 1984, Inf. Syst..

[25]  Abraham Kandel,et al.  Implementing Imprecision in Information Systems , 1985, Inf. Sci..

[26]  George J. Klir,et al.  Fuzzy sets, uncertainty and information , 1988 .

[27]  N. C. Hsieh,et al.  Fuzzy information in fuzzy relational database , 1997 .

[28]  Juan Miguel Medina,et al.  Towards the implementation of a generalized fuzzy relational database model , 1995, Fuzzy Sets Syst..

[29]  Didier Dubois,et al.  The treatment of uncertainty in knowledge‐based systems using fuzzy sets and possibility theory , 1988, Int. J. Intell. Syst..