Special Issue Article Open Access

Extracting the Information by Ranking Techniques to Increase the Privacy of Search Engine

Abstract

An increasing number of databases have become web accessible through HTML form-based search interfaces. The data units returned from the underlying database are usually encoded into the result pages dynamically for human browsing. For the encoded data units to be machine process able, this is essential for many applications such as deep web data collection and Internet. Comparison shopping, they need to be extracted out and assigned meaningful labels. In this paper, we present an automatic annotation approach that first aligns the data units on a result page into different groups such that the data in the same group have the same semantic. The ability to accurately judge the semantic similarity between words is critical to the performance of several applications such as Information Retrieval and Natural Language Processing. Therefore, in this paper we propose a semantic similarity measure that uses in one hand, an online English dictionary provided by the Semantic Atlas project of the French National Center for Scientific Research (CNRS) and on the other hand, a page counts based metric returned. The ranking techniques and login security concepts for increase the efficiency and privacy of search engine.

C.Parimala, Prof.B.Sakthivel

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