Enhancing the Privacy Protection of the User Personalized Web Search Using RDF
Abstract— Personalized searches refers to search experiences that are tailored specifically to an individual's interest by incorporating information about the individual beyond specific query provided. User may not aware of some privacy issues in search results where personalized and wonder why things that are interested in have become so relevant. Such irrelevance is largely due to the enormous variety of user’s contexts and backgrounds, as well as the ambiguity of texts. In contrast, Profile-based methods can be potentially effective for almost all sorts of queries, but are reported to be unstable under some circumstances. The amount of structured data available on the web has been increasing rapidly, especially RDF data. This proliferation of RDF data can also be attributed to the generality of the underlying graph-structured model, i.e., many types of data can be expressed in this format including relational and XML data. For a Personalized Semantic Web Search the semi structured data should be indexed with RDF. This proposed RDF technique not only enhances the privacy and security of the user profile and optimizes query for efficient filtering of data. The user profile access is been avoided by means of placing a proxy in the client side, so profile exposure avoided. The proxy generates a random profile at each time. The contents will be sent back to the proxy and only the relevant contents will be sent over to the client. In this RDF framework the queries are semi structured for personalized web search.