Abstract
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.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Journal of Advanced Computational Intelligence and Intelligent Informatics
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
