Database exploration accommodating fuzzy information퍼지 정보를 수용하는 데이타베이스 탐사 기법

Database exploration means activities examining the database thoroughly to acquire potentially useful information. Especially, the data mining facility discovering knowledge that is implicit, but obtainable through systematic data processing, is one of essential constituents of database exploration. The importance of data mining is emphasized, since rapidly increasing size of data makes direct exposure of raw records no longer so helpful. In addition, treatment of fuzzy information must be incorporated into database exploration facilities to cope with ubiquitous fuzziness in actual domain, and in turn, provide more effective functionality. In this thesis, we investigate database exploration techniques accommodating fuzzy information. Firstly, Level-1 Fuzzy Relational Data Model (FRDM-1) is proposed as a theoretically clear framework for processing fuzzy queries. It is hard to make a crisp query reflecting the user``s data request exactly, against a large amount of data. Fuzzy querying capability is regarded as a basic form of database exploration, since users can express their data requests with their own subjective linguistic and flexible terms. Furthermore, the ranked answer for a fuzzy query provides useful information to understand content of the database. Secondly, an interactive top-down data mining process for database summarization is devised. The process exploits fuzzy domain knowledge to hypothesize discovery targets and evaluate the validity of each hypothesis. Thirdly, the top-down data mining process is extended to discover inter-attribute relationships. Finally, the data mining process is integrated with FRDM-1 to allow more flexibility in user``s exploration request. FRDM-1 is established by two basic query languages, i.e., Level-1 Fuzzy Relational Algebra(FRA-1) and Level-1 Fuzzy Relational Calculus(FRC-1). In addition, two advanced query languages, i.e., Fuzzy Selective Relational Algebra(FSRA) and Fuzzy Selective Relational Calculus(FSRC...
Advisors
Kim, Myoung Ho(김명호)researcher
Publisher
한국과학기술원
Issue Date
1995
Identifier
101792/325007 / 000925243
Language
eng
Description

학위논문(박사) - 한국과학기술원 : 전산학과, 1995.8, [ x, 118 p. ]

Keywords

Data Mining; Fuzzy Database; Knowledge Discovery in Databases; 데이타베이스 지식 발견; 데이타 채광; 퍼지 데이타베이스

URI
http://hdl.handle.net/10203/33048
Link
http://library.kaist.ac.kr/search/detail/view.do?bibCtrlNo=101792&flag=t
Appears in Collection
CS-Theses_Ph.D.(박사논문)
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