A Pruning Algorithm for Improving Web Resources Searching and Classification in Knowledge Management-Based Web Systems
نویسندگان
چکیده
Knowledge Management-based Web Systems (KM -bWS) are a novel class of Web Information Systems whose main goal is to adapt contents and presentations with respect to user needs and backgrounds through the execution of Knowledge Management processes. A KM-bWS can be seen as an “intelligent knowledge hub” because it makes distributed Web resources available by means of Knowledge Management techniques such as classification and clustering. In this paper we present a reference architecture for KM-bWS, and a pruning algorithm, called KM_search, that allows to improve Web resources searching and classification. This algorithm evaluates the relevance of Web resources for different classes of users, by matching search keywords with the content of Web pages. The Web page section where keywords are found as well as the position of the page inside the search tree both concur in the evaluation of Web resources relevance.
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