Conceptual Information Extraction with Link-Based Search

Abstract

Link-based search provides a new vehicle to find relevant web documents on the WWW. Recently, there is quite a bit of optimism that the use of link information can improve search quality as in Google. Usually, text-based search engine returns web sites which have simply the best frequency of user query, so that the result might be different from user’s expectation. However, hypertextual search engine finds the most authoritative site. Proposed search engine consists of crawling, storing of link structure, ranking, and personalization processes. User profile encodes different relevances among concepts for each user. For conceptual information extraction from link-based search engine, fuzzy concept network is adopted. Fuzzy concept network can be personalized using the profile information and used to conduct fuzzy information retrieval for each user. By combining personal fuzzy information retrieval and link-based search, proposed search agent provides high-quality information on the WWW about user query. To show the effectiveness of the proposed search engine, a subjective test for five persons is conducted and the result is summarized. The result for five persons shows the usefulness of the proposed system and possibility for personalized conceptual information extraction.