Enhancing the power of Web search engines by means of fuzzy query
Decision Support Systems - Web retrieval and mining
Personalized local internet in the location-based mobile web search
Decision Support Systems
User modeling for personalized Web search with self-organizing map: Research Articles
Journal of the American Society for Information Science and Technology
User modeling for personalized Web search with self-organizing map: Research Articles
Journal of the American Society for Information Science and Technology
Toward an intelligent local web search in telematics
KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part I
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Traditional World Wide Web search engines, such as AltaVista.com, index and recommend individual Web pages to assist users in locating relevant documents. As the Web grows, however, the number of matching pages increases at a tremendous rate. Users are often overwhelmed by the large answer set recommended by the search engines. Also, if a matching document is a hypertext, the document structure is destroyed and the individual pages that compose the document are returned instead. The logical starting point of the hyperdocument is thus hidden among the large basket of matching pages. Users need to spend a lot of effort browsing through the pages to locate the starting point, a very time consuming process. This paper studies the anchor point indexing problem. The set of anchor points of a given user query is a small set of key pages from which the larger set of documents that are relevant to the query can be easily reached. The use of anchor points helps solve the problems of huge answer set and low precision suffered by most search engines by considering the hyperlink structures of the relevant documents, and by providing a summary view of the result set.