|Author:||Cheung, Alan Chun-lun|
|Title:||Data mining for the development of a fuzzy rule based query system|
Hong Kong Polytechnic University -- Dissertations
|Pages:||118 leaves : ill. ; 30 cm|
|Abstract:||Database processing has now been the largest domain of application of information processing all around the world. Querying is always a major domain of application of database system. Information is to be retrieved from a database, no matter in the case of routine and simple daily retrieval or in the case of large scale knowledge acquisition from database. However, in the field of query processing and database modelling, rare studies is made to improve database modelling so as to enhance information retrieval and knowledge acquisition. This paper, based on Codd's work on relational database model and some state-of-art knowledge acquisition technique, is attempted to highlight and implement fuzzy and inference technique in data-mining and query processing. Also, this paper will introduce, based on Standard Query Language, a Fuzzy Query Language to conduct imprecise querying. This paper will focus on 2 areas : 1) Apply technique to extract fuzzy rules from database. 2) Implement fuzzy rule based query processing technique. Fuzzy knowledge and technique is more commonly studied and successfully implemented in the area of control, pattern recognition and classification. Different from most of the previous studies on fuzzy technique, this paper put focus on implementing technique to discover fuzzy rule from database and make use of these rule to conduct query processing. Therefore, significant overlapping of research topic with other researcher is not to be expected. This paper will introduce a framework of prototype of a fuzzy rule based database model and query system. In the mid of the paper it will implement the suggested prototype and analysis on the suggested prototype/technique is placed at the end of the paper. This research suggests a more intelligent way of information storage, retrieval as well as knowledge acquisition from database. The enrichment of AI or fuzzy feature in database management system helps to handle data analysis or query at conceptual level with an optimal speed which cannot be handled effectively by classical approach. Applying this technique in reality can help building a more knowledge-rich database system and saving cost and effort in handling query and data analysis. It also can help users to explore 'hidden' knowledge in a database which cannot be easily be highlighted or discovered manually.|
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