A NEW WORD-INTERSECTION CLUSTERING METHOD FOR INFORMATION FILTERING
Mao Lin Huang, Jun Lai, Ben Soh · 2004
As the use of the web grows globally and exponentially, it becomes increasingly harder for users to find the information they want. Therefore, there is a need for good information filtering mechanisms. This paper presents a new, efficient information filtering method using word clusters. Traditional filtering methods only consider the relevance values of document. As a result, these conventional methods fail to consider the efficiency of document retrieval, which is also crucial. Our algorithm using offline computation attempts to cluster similar documents based on words shared by documents to produce clusters, so that the efficiency of information filtering and retrieval can be improved. Abstract: