Improving Web Search Result using Semantic Similarity with Re-ranking
A. V. Deorankar, Prashant N. Chatur · 2012
The Aim of this paper is to re-ranking the web search result using semantic similarity to improve the quality of search engines. First obtain top N results returned by search engine such as Google, and then use semantic similarities between the Content obtain from the web search result and the users query. A semantic similarity algorithm based on WordNet ontology which is used to calculate the similarity of each snippet to each of the return result. And then based on the similarity re-ranking is performed. A balanced similarity ranking method combined with Google’s rank. Here first we convert the ranking position to an importance score for semantics instead of keyword matching which can better adapt timeliness of the pages is used to rank these Web pages.