Design of a Visualized Information Retrieval Assistance System Based On Graphic Clustering
碩士 === 大葉大學 === 資訊管理學系碩士班 === 96 === Each kind of fast distributed information through computer networks mutually interacts and forms new knowledge nowadays. However, all full-text information retrieval systems such as Google have no suitable mechanisms to synthesize correlated glossaries and to ill...
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| Other Authors: | |
| Format: | Others |
| Language: | zh-TW |
| Published: |
2008
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| Online Access: | http://ndltd.ncl.edu.tw/handle/54569165150605596050 |
| Summary: | 碩士 === 大葉大學 === 資訊管理學系碩士班 === 96 === Each kind of fast distributed information through computer networks mutually interacts and forms new knowledge nowadays. However, all full-text information retrieval systems such as Google have no suitable mechanisms to synthesize correlated glossaries and to illustrate their global information structures. To simulate human knowledge concepts from the connections of a vocabulary graph, it was attempted to construct reasoning patterns of information by applying a graph-based clustering algorithm to classify and induce more information, and by using colored indication to auxiliary mark up important vocabularies.
A visualized information retrieval assistance system was designed and implemented based on the mentioned concepts above. The proposed system can assist users to retrieve information more intuitively and following the knowledge constitution way. Finally, a questionnaire survey was used to evaluate the satisfaction degrees of system users. Some achievements are reached as following:
1.A visualized information retrieval assistance system was implemented to visually present information and to moderately guide users in retrieving information.
2.Correlated glossaries are acquired and organized through Internet to assist users to understand the related knowledge of searching keywords.
3.Users are guided to retrieve information more precisely by clustering related glossaries to provide the information of important vocabularies and previous retrieval paths.
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