| Summary: | 碩士 === 國立彰化師範大學 === 資訊工程學系 === 99 === Recently, with the physical network technology developing, there are more and more users take search engines as the information acquired entrance. Accompany with the amount of data being larger and larger, the information explosion has been a big trouble. Most of those search engines which online serviced are keywords-based search, one of their drawback is “semantic”, keywords-based search engine cannot judge a vocabulary which mean it’s represented. Cause of the same vocabulary in difference domain maybe having different meanings. The others drawbacks of online search engine are vocabulary’s importance and user’s opinions, most of those online search engines considered each vocabulary’s importance as similarly. It’s maybe conflict with user’s opinions. To conquer these problems, this thesis proposes a new type search engine which developed based on semantic technique and fuzzy theory. First, we constructed a fuzzy ontology as our knowledge base and involved fuzzy logic to represent the relationship which between term and term. Second, we develop web crawler to fetch webpage automatically. Finally, we allow user to set multiple vocabularies 、each vocabulary’s importance and six parameters , when these query instructions submit, system will search those vocabularies which related with user defined, and then these vocabularies which together with user defined and system found are regard as the input query command to search webpage, after search execution terminate, system execute fuzzy aggregation with those web pages and parameters which user defined to obtain the final ranking and display result.
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