NDLI: Mining approximate dependency to answer null queries on similarity-based fuzzy relational databases

Content Provider	IEEE Xplore Digital Library
Author	Shyue-Liang Wang Tzung-Pei Hong
Copyright Year	2000
Description	Author affiliation: Dept. of Inf. Manage., I-Shou Univ., Kaohsiung, Taiwan (Shyue-Liang Wang)
Abstract	Null queries are queries that elicit a null answer from the database. In possibility-based fuzzy relational database model, a theoretical framework utilizing analogical reasoning and fuzzy functional dependency to answer null queries has been proposed by Dutta (1991). However, no searching algorithm is provided to discover the fuzzy functional dependencies among attributes. In this work, we extend the concept of fuzzy functional dependency to approximate dependency on similarity-based fuzzy relational data model. In addition, we proposed a data mining algorithm to discover all the approximate dependencies among attributes. It therefore can automatically obtain approximate answers for null queries and missing data values in an incomplete database. This kind of facility will certainly improve the cooperative nature of databases and enhance the user-friendliness of the database systems.
Starting Page	615
Ending Page	620
File Size	446241
Page Count	6
File Format	PDF
ISBN	0780358775
ISSN	10987584
DOI	10.1109/FUZZY.2000.839063
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2000-05-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Relational databases Data models Fuzzy reasoning Database systems Inference algorithms Information management Data mining Fuzzy systems Artificial intelligence Target recognition
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Artificial Intelligence Theoretical Computer Science Software

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