We present an approach for the evaluation of a term significance model, Gain Of Words (GOW)#N# using two different web search engines (WSEs) : Google1 and Yahoo2 . Our term association model#N# extracts significant terms from a single document without using a corpus. We extract the significant terms from the Gain of Words (GOW) parameters’ values based on a sentence level analysis of#N# the document. The experiment is modeled by three sets of queries for the search engines, as single#N# queries, paired queries and triplet queries. The evaluation is based on the documents retrieved from#N# the WSEs using these queries. The results show that the terms or words of higher rank according to#N# this model extract more relevant documents from the WSE as shown through the similarity results#N# with the source documents from where the terms were extracted. We have shown that our model#N# works better than the term frequency inverse sentence frequency (TFISF) model using WSE rankings.
['Sukanya Manna', 'Tom Gedeon']
Web Search Engines A Basis For Term Evaluation