Web search engines capitalize on, or lend themselves to, the construction of user interest profiles to provide personalized search results. The lack of transparency about what information is stored, how it is used and with whom it is shared, limits the perception of privacy that users have about the search service. In this thesis, we investigate a technology that allows users to replace specific queries with more general but semantically similar search terms.
Through the generalization of queries, the user profile becomes less precise and therefore more private, although evidently at the expense of a degradation in the accuracy of the search results. In this work, we design and develop a tool that implements this principle in real practice. PrivacySearch, developed as a browser plug-in for Google Chrome, enables users to generalize the queries sent to a search engine in an automated fashion, without the need for any kind of infrastructure or external databases, and in real time, according to simple and intuitive privacy criteria.
Copyright 2018 Francisco Javier Rodrigo Ginés
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