Improving Web Search Results Using Semantic Clustering

This paper consider the problem of search engine that are not capable of retrieving appropriate result on query given. Most of the users are not able to give the appropriate query to get what exactly they wanted to retrieve. So the search engine retrieves a massive list of data, which are ranked by the page rank algorithm or relevancy algorithm or human judgment algorithm. If the relevant results do not occur in the first part of results returned then user may fail to find them. The possible solution for this problem is to cluster the search results using an algorithm called Semantic Suffix Tree Clustering. This algorithm constructs suffix tree by using semantic similarity and word matching. This paper also analyzes the lingo algorithm, suffix tree algorithm and semantic suffix tree algorithm through some results. Keywords— Semantic suffix tree, semantic search results clustering, search result clustering.