SCHISM—A Web search engine using semantic taxonomy

The majority of the current search engines generate a huge list in reply to a user query. This result is normally ranked by using ranking criteria such as page rank or relevancy to the query. However, this list is extremely inconvenient to users, since it expects them to look into each page sequentially in an exhaustive manner to find the relevant information. As a result, most users only search for an initial few Web pages on the list. Thus many other relevant information can be overlooked. The clustering method is one such solution to overcome this problem. Instead of a sequential list, it groups the search results into clusters and labels these with representative words for each cluster. These labeled clusters of search results are exposed to users. The clustering method provides benefits in terms of reduced size of information provided to the end users.