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The Pennsylvania State University, Harrisburg
School of Business Administration
Capital College

Supporting Privacy Protection in Personalized Web Search

A Master’s Paper
By:
Naga Manoswitha Kasula

Submitted in Partial Fulfillment of the Requirements for the Degree of
Master of Science in Information Systems

Date: ________________

COURSE: INFSY 554
MASTER 'S PAPER APPROVAL

Author:

__________________________________________ ____________________ Signature Date

Approval:
Name and Title of Course Supervisor:

Dr. Girish H. Subramanian
Professor of Information Systems

_________________________________________ _____________________ Signature Date TITLE PAGE NO
Summary
4
Objective
5
Background
Literature Review
5
6
Java
6
JDBC
7
MySql
7
JSP
HTML
8
8
Research Design Unified Modeling Language Database Design
9
10
11
Conclusion
References
10
11

Contents

Summary
Today’s age is the world of technologies, where lots of inventions and discoveries have made everyone to rely on the use of latest technology. Not all users of Internet are willing to reveal the information they are browsing on their mobile devices or any other electronic gadgets. There is certain information which they are reluctant to share. Personalized Web Search (PWS) has demonstrated its effectiveness in improving the quality of various search services over the Internet. However, users’ are reluctant to reveal their private information during the web search. This has become a major barrier for the wide proliferation of PWS. Supporting privacy protection in personalized web search is an application which helps the users in customizing the information user browses. User can manage the revelation of the browsing history and customize it passing certain rules. In the application, PWS framework



References: Shou, L., Bai, He., Chen, K., & Chen, G. (2014). Supporting privacy protection in personalized web search. IEEE Transactions on Knowledge and Data Engineering. Vol.: 26, No. 2. pp. 453-467. Retrieved from http://ieeexplore.ieee.org.ezaccess.libraries.psu.edu/stamp/stamp.jsp?tp=&arnumber=632 9891 Dou, Z., & Song, R. (2007). A large-scale evaluation and analysis of personalized search strategies. Proceedings of the 16th International Conference on World Wide Web. pp. 581-590. Retrieved from http://dl.acm.org/citation.cfm?id=1242651 Teevan, J., Dumais, S. T., & Horvitz, E. (2005). Personalizing search via automated analysis of interests and activities. Proceedings of the 28th International ACM SIGIR Conference Research and Development in Information Retrieval (SIGIR). pp. 449-456. Retrieved from http://research.microsoft.com/en-us/um/people/sdumais/sigir2005- personalizedsearch.pdf Liang, Y. D. (2015). Introduction to java programming-brief version. 10th edition. Urma. R., Fusco, M., & Mycroft, A. (2015). Java 8 in action- lamdas, streams, and functional- style programming. Edition 1st. Web services tutorials. W3schools.com. Retrieved from http://www.w3schools.com/webservices/default.asp The Java Tutorials. Oracle Java Documentation. Retrieved from docs.oracle.com/javase/tutorial/jdbc/basics/ The unified modeling language. Retrieved from http://www.uml-diagrams.org/

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