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Supporting Privacy Protection in Personalized Web Search

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The proposed personalized mobile search engine is an innovative approach for personalizing web search results. By mining content concepts for user profiling, it utilizes both the content preferences to personalize search results for a user.



  • Data mining



We propose a personalized search engine that captures the users’ preferences in the form of concepts by mining their clickthrough data. Due to the importance of location information in mobile search, PSE classifies these concepts into content concepts. The user preferences are organized in an ontology-based, multifacet user profile, which are used to adapt a personalized ranking function for rank adaptation of future search results. In our design, the client collects and stores locally the clickthrough data to protect privacy, whereas heavy tasks such as concept extraction, training, and reranking are performed at the server. Moreover, we address the privacy issue by restricting the information in the user profile exposed to the server with two privacy parameters.


 Existing System:

In existing there is no reranking of information and no security for the user search result.



  • The number of users and queries in the experiments are small. This means that the results from the experiments cannot be construed as representative in diverse situations.
  • Since users are given with predefined queries and topical interests, they have to synthesize their information needs from the given queries and topical interests and conduct their searches correspondingly.
  • Thus, their searches behaviors in the experiments may be quite different from what they might have exhibited when they attempt tore solve real-life information needs.


 Proposed System:

It profiles both of the user’s content in the ontology based user profiles, which are automatically learned from the clickthrough without requiring extra efforts from the user.

We propose and implement a new and realistic design for Personilization. To train the user profiles quickly and efficiently.

PSE addresses this issue by controlling the amount of information in the client’s user profile being exposed to the server using two privacy parameters, which can control privacy smoothly, while maintaining good ranking quality.



  • The proposed one is an innovative approach for personalizing websearch results. By mining content and location concepts for user profiling, it utilizes both the content and location preferences to personalize search results for a user.
  • It studies the unique characteristics of content concepts, and provides acoherent strategy using client-server architecture to integrate them into a uniform solution for the environment.


Hardware Specification:

  • 1 GB RAM
  • 80 GB Hard Disk
  • Intel Processor
  • Datacard for Static IP
  • Internet Connection


Software Specification:

  • Windows OS(7-32 bit)
  • JDK 1.7
  • Apache Tomcat 7
  • Eclipse
  • MySql server
  • SQLyog


Architecture Diagram:

Privacy Protection in Personalized Web Search

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  • Price
  • Instructor pantech team
  • Duration 15 Hrs
  • Enrolled 0 student
  • Access 3 Months

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