Answering Null Queries by Analogical Reasoning on Similarity-based Fuzzy Relational Databases
Shyue-Liang Wang,* Tzung-Pei Hong,** and Wen-Yang Lin*
*Department of Information Management I-Shou University Kaohsiung, 84008, Taiwan, ROC.
**Department of Electrical Engineering National University of Kaohsiung Kaohsiung, Taiwan, ROC.
We present here a method of using analogical reasoning to infer approximate answers for null queries on similarity-based fuzzy relational databases. Null queries are queries that elicit a null answer from a database. Analogical reasoning assumes that if two situations are known to be similar in some respects, it is likely that they will be similar in others. Application of analogical reasoning to infer approximate answers for null queries using fuzzy functional dependency and fuzzy equality relation on possibility-based fuzzy relational database has been studied. However, the problem of inferring approximate answers has not been fully explored on the similarity-based fuzzy relational data model. In this work, we introduce the concept of approximate dependency and define a similarity measure on the similaritybased fuzzy model, as extensions to the fuzzy functional dependency and fuzzy equality relation respectively. Under the framework of reasoning by analogy, our method provides a flexible query answering mechanism for null queries on the similarity-based fuzzy relational data model.