A Document Clustering Approach for Search Engines
Chun‐Wei Tsai, Ting-Wen Liang, Jiun-Huei Ho, Chu‐Sing Yang, Ming‐Chao Chiang · 2006
This paper presents a new internet search engine system called document clustering for search engines (DCSE). This system focuses on overcoming the following challenges faced by search engines: (1) relevance of the search results in response to a user query and (2) information coverage. The DCSE system is based upon a meta-search engine that integrates information retrieval (IR), information extraction (IE), genetic algorithm (GA) and document clustering algorithm into a single system. DCSE utilizes information extraction techniques and vector space model (VSM) calculations to determine the relevance of various data, and then categorizes the data via information retrieval and document clustering algorithm in order to better refine the result. Users will receive information that has been calculated and sorted and web links that are ranked according to their relevance. The end result will reduce the amount of time that users spend filtering out irrelevant data.