Web search results are far from perfect due to the polysemous and synonymous
characteristics of nature languages, information overload as the results of information …

This research combines Web snippet categorization, clustering and personalization
techniques to recommend relevant results to users. RIB–Recommender Intelligent Browser …

Abstract Information retrieval systems like web search engines can be used to meet the
user's information needs by searching and retrieving the relevant documents that match the …

Current web search engines, such as Google, Bing, and Yahoo!, rank the set of documents
S retrieved in response to a user query and display the URL of each document D in S with a …

This paper details a modular, self-contained web search results clustering system that
enhances search results by (i) performing clustering on lists of web documents returned by …

With so much information available on the web, looking for relevant documents on the
Internet has become a tough task. In this paper we present as approach which is a match …

Rating a page to be a best one, based only on Page Ranking algorithm of Brin and Page
would be insufficient. This method relied totally on Link information alone. However, due to …

Short and ambiguous queries are the major problems in search engines which lead to
irrelevant information retrieval for the users' input. The increasing nature of the information …

Targeting useful and relevant information on the internet is a highly complicated research
area, which is served in part by research into document clustering. A foundational aspect of …

The problems of information overload and vocabulary differences have become more
pressing with the emergence of increasingly popular Internet services. The main information …