Short note on Web Document Clustering.

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 Web Document Clustering

Web document clustering is another approach to finding relevant documents on a topic or query keywords. As discussed earlier, the popular search engines often return a huge, unmanageable list of documents that contain the keywords that the user-specified. Finding the most useful documents from such a large list is usually tedious, often impossible. The user could apply clustering to a set of documents returned by a search engine in response to a query with the aim of finding semantically meaningful clusters, rather than a list of ranked documents, that are easier to interpret. It is not necessary to insist that a document can only belong to one cluster since in some cases it is justified to have the document belong to two or more clusters. Web clustering may be based on content alone, may be based on both content and links, or may be excluded based on links.

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