Issues and Challenges in Measuring Security Threats During Personalized Web Search
Keywords:
PWS, Security threats, ODP MetadataAbstract
The World Wide Web is an important source of data that can come either from the Web content, represented by the billions of pages publicly available, or from the Web usage, represented by the log information daily collected by all the servers around the world. The continuous growth in the size and use of the World Wide Web imposes new methods of design and development of online information services. Most Web structures are large and complicated and users often miss the goal of their inquiry, or receive ambiguous results when they try to navigate through them. On the other hand, the e-business sector is rapidly evolving and the need for Web marketplaces that anticipate the needs of the customers is more evident than ever. Therefore, the requirement for predicting user needs in order to improve the usability and user retention of a Web site can be addressed by personalizing it. This paper tries to address some issues regarding some of the major challenges faced by Search Engines.
References
D. Pierrakos, G. Paliouras, C. Papatheodorou, CD. Spyropoulos, “Web usage mining as a tool for personalization: A survey”, User modeling and user-adapted interaction, Vol.13, Issue.4, pp.311-317, 2003.
Z. Ma, G. Pant, OR. Sheng, “Interest-based personalized search”, ACM Transactions on Information Systems (TOIS), Vol.25, Issue.1, pp.1-5, 2007.
OP. Attanasio, N. Pavoni, “Risk sharing in private information models with asset accumulation: Explaining the excess smoothness of consumption”, Econometrica, Vol.79, Issue.4, pp.1027-1068, 2011.
Y. Xu, K. Wang, B. Zhang, Z. Chen, “Privacy-enhancing personalized web search”, In Proceedings of the 16th international conference on World Wide Web, Canada, pp. 591-600, 2007.
J. FOLEY, Are Google searches private? An originalist interpretation of the fourth amendment in online communication cases. Journal of Berkeley Technology, Vol.22, Issue.1, pp.447–472, 2007.
Glen Jeh, Jennifer Widom, “Scaling personalized web search with Relevance Feedback”, In Proceeding of the 12th International World Wide Web Conference (WWW), Hungary, pp.1-35, 2003.
S. NainB, H. Lall, “Deep Web Data Scraper: Search Engine”, International Journal of Computer Sciences and Engineering, Vol.2, Issue.5, pp.52-56, 2014.
M. Barbaro, T. Zeller, “A face is exposed for AOL searcher no. 4417749”, In The New York Times, NY, pp.1-86, 2006.
H.R. Kim, Philip K. Chan, “Learning implicit user intentions for context in personalization”, In Proc. Of International Conference on Intelligent User Interface (IUI), Florida, pp.54-89, 2003.
D. Howe, H. Nissenbaum, “Trackmenot: Achieving User Intentions in web search”, In On the Identity Trail: Privacy Anonymity and Identity in a Networked Society (Oxford University Press), Oxford, pp.1-40, 2008.
KW. Leun, DL. Lee, W. Ng, HY. Fung, “A framework for personalizing web search with concept-based user profiles”, ACM Transactions on Internet Technology (TOIT), Vol.11, Issue.4, pp.1-17, 2012.
N. Cao, C. Wang, M. Li, K. Ren, W. Lou, “Privacy-preserving multi-keyword ranked search over encrypted cloud data”, IEEE Transactions on parallel and distributed systems, Vol.25, Issue.1, 222-233, 2014.
Miguel-Angel Sicilia, MD. Lytras, “Metadata and Semantics”, Springer Science & Business Media, USA, pp.1-550, 2008
Downloads
Published
How to Cite
Issue
Section
License
This work is licensed under a Creative Commons Attribution 4.0 International License.
Authors contributing to this journal agree to publish their articles under the Creative Commons Attribution 4.0 International License, allowing third parties to share their work (copy, distribute, transmit) and to adapt it, under the condition that the authors are given credit and that in the event of reuse or distribution, the terms of this license are made clear.
