Week 12 - Intelligent Information Retrieval - Reading Note

This week I read,

1. Susan Gauch, Mirco Speretta, Aravind Chandramouli and Alessandro Micarelli. User Profiles for Personalized Information Access. Chapter 2 in  Brusilovsky, P., Kobsa, A., Neidl, W. (eds.) (2007) The Adaptive Web: Methods and Strategies of Web Personalization. Lecture Notes in Computer Science, Vol. 4321. Springer-Verlag, Berlin Heidelberg New York.
2. Michael J. Pazzani and Daniel Billsus. Content-Based Recommendation Systems. Chapter 10 of  Brusilovsky, P., Kobsa, A., Neidl, W. (eds.) (2007) The Adaptive Web: Methods and Strategies of Web Personalization. Lecture Notes in Computer Science, Vol. 4321. Springer-Verlag, Berlin Heidelberg New York.
3. Ahn, J., Brusilovsky, P., He, D., Grady, J., and Li, Q.  (2008). Personalized web exploration with task models. In Proceeding of the 17th international Conference on World Wide Web (Beijing, China, April 21 - 25, 2008). WWW '08. ACM, New York, NY, 1-10. DOI= http://doi.acm.org/10.1145/1367497.1367499.
4. He, D., Brusiloviksy, P., Grady, J., Li, Q., and Ahn, J. (2007). How Up-to-date should it be? the Value of Instant Profiling and Adaptation in Information Filtering. In Proceedings of the IEEE/WIC/ACM international Conference on Web intelligence(November 02 - 05, 2007). Web  Intelligence. IEEE Computer Society, Washington, DC, 699-705. DOI= http://dx.doi.org/10.1109/WI.2007.135

From 1, user profiling is a way to narrow the scope of information avaliable based on some known information about the user. However, this requires the system to collect information about users, a potential privacy concern. Many people choose to opt out of these systems when given a chance.

From 2, content based recommendation systems are used to pair down the set of results to just the best to show a user. Think Netflix recommendations. Recommendations are usually driven from a user profile. 

Many techniques for making recommendations.

From 3, an alternate model for personalized search is task-based search. System attempts to gather information about the task, or information need, that the user is currently exploring over several searches. 

From 4, examines how often to refresh personalized results and user profiles. Real-time as a user is searching or just occasionally. Research shows that the real-time updates allow users to complete tasks faster. However, the speed comes at the cost of accuracy and user satisfaction.