A Novel Approach to Improve the Accuracy of Web Retrieval

Abstract

General purpose search engines utilize a very simple view on text documents: They consider them as bags of words. It results that after indexing, the semantics of documents is lost. In this paper, we introduce a novel approach to improve the accuracy of Web retrieval. We utilize the WordNet and WordNet SenseRelate All Words Software as main tools to preserve the semantics of the sentences of documents and user queries. Nouns and verbs in the WordNet are organized in the tree hierarchies. The word meanings are presented by numbers that reference to the nodes on the semantic tree. The meaning of each word in the sentence is calculated when the sentence is analyzed. The goal is to put each noun and verb of the sentence on the right place on the tree. Taking this information into account, it is possible to solve the ambiguity problem for the query keywords and create the indicative summaries taking into account query words, and semantically related hypernyms and synonyms.