Abstract: Web search engines (e.g. Google, Yahoo etc.) are widely used to find certain data among a huge amount of information in a nominal amount of time. However, these useful tools also pose a privacy threat to the end user’s web search engines profile their end user’s by storing and analyzing past searches submitted by them. In the introduced system, we can implement the String Similarity Matching Algorithm (SSM Algorithm) for improving the better search quality results. To address this privacy threat, present solutions introduce new mechanisms that introduce a high cost in terms of calculation and communication. Personalized search is a promising way to get better accuracy of web search, and has been attracting more attention recently. However, effective personalized search needs collecting and aggregating user information, which often increases serious concerns of privacy infringement for many users. Indeed, these concerns have become one of the main barriers for deploying personalized search applications, and how to do privacy-preserving personalization is a great challenge. In this we introduce and try to resist adversaries with broader background knowledge, such as richer relationship amongst topics. Richer relationship means we generalize the user profile results by using the background knowledge which is going to save in history. Through this we can hide the user search results. By using this mechanism, we can achieve the privacy.
Keywords: Privacy protection, Data Mining, Result retrival, Profile, generalization, Online Anonymity, IR evaluation, Automatic Identification.
Title: Secure and Proficient Web Search Using String Matching Algorithm
Author: Deepika Sisode, Pooja Agrawal, Pratiksha Thorat, Chaitali Umap, Prof. Arati Deshpande
International Journal of Computer Science and Information Technology Research
ISSN 2348-1196 (print), ISSN 2348-120X (online)
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