Web document clustering using a hybrid neural network
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The list of documents returned by Internet search engines in response to a query these days can be quite overwhelming. There is an increasing need for organising this information and presenting it in a more compact and efficient manner. This paper describes a method developed for the automatic clustering of World Wide Web documents, according to their relevance to the user’s information needs, by using a hybrid neural network. The objective is to reduce the time and effort the user has to spend to find the information sought after. Clustering documents by features representative of their contents—in this case, key words and phrases—increases the effectiveness and efficiency of the search process. It is shown that a two-dimensional visual presentation of information on retrieved documents, instead of the traditional linear listing, can create a more user-friendly interface between a search engine and the user.
|Publication Type:||Journal Article|
|Murdoch Affiliation:||School of Information Technology|
|Copyright:||© 2004 Elsevier B.V.|
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