| Summary: | 碩士 === 元智大學 === 電機工程學系 === 90 === In the real world, many information systems and applications must deal with imprecise or vague data. For such systems, fuzzy logic theory is well-known to provide a framework for modeling flexibility and handling vagueness in the interface between human conceptual categories and data, which is similar to the natural language. Such capabilities have been already developed in the database field, especially for handling flexible queries.
In this thesis, we present the applications of fuzzy relational databases using similarity-based and possibility-based approaches to handle imprecise information. With two cases for XML documents retrieval and decision making, we propose a fuzzy XML query language, an extension of XML-QL called XML-FQL, for XML documents retrieval and apply flexible query based on the fuzzy measure approaches to realize the possibility retrieval.
For the case of XML documents retrieval, the XML-FQL we proposed is a well-defined fuzzy query language for XML documents to handle some of element or attribute values that are more similar and allow the functions of flexible query to retrieve an ordered list by similarity. For the case of decision making, we have applied fuzzy theory to perform some flexible queries for merging many different opinions gathered from various experts’ questionnaires.
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