| Learning users' interests by unobtrusively observing their normal behavior |
| Full text |
Pdf
(558 KB)
|
| Source
|
International Conference on Intelligent User Interfaces
archive
Proceedings of the 5th international conference on Intelligent user interfaces
table of contents
New Orleans, Louisiana, United States
Pages: 129 - 132
Year of Publication: 2000
ISBN:1-58113-134-8
|
|
Authors
|
|
Jeremy Goecks
|
Computer Sciences Dept., University of Wisconsin, 1210 W. Dayton Street, Madison, WI
|
|
Jude Shavlik
|
Computer Science Dept., University of Wisconsin, 1210 W. Dayton Street, Madison, WI
|
|
| Sponsors |
|
| Publisher |
|
| Bibliometrics |
Downloads (6 Weeks): 15, Downloads (12 Months): 90, Citation Count: 29
|
|
|
ABSTRACT
For intelligent interfaces attempting to learn a user's interests, the cost of obtaining labeled training instances is prohibitive because the user must directly label each training instance, and few users are willing to do so. We present an approach that circumvents the need for human-labeled pages. Instead, we learn “surrogate” tasks where the desired output is easily measured, such as the number of hyperlinks clicked on a page or the amount of scrolling performed. Our assumption is that these outputs will highly correlate with the user's interests. In other words, by unobtrusively “observing” the user's behavior we are able to learn functions of value. For example, an intelligent browser could silently observe the user's browsing behavior during the day, then use these training examples to learn such functions and gather, during the middle of the night, pages that are likely to be of interest to the user. Previous work has focused on learning a user profile by passively observing the hyperlinks clicked on and those passed over. We extend this approach by measuring user mouse and scrolling activity in addition to user browsing activity. We present empirical results that demonstrate our agent can accurately predict some easily measured aspects of one's use of his or her browser.
REFERENCES
Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.
| |
1
|
T. Joachims, D. Freitag, and T. Mitchell. WebWatcher: A Tour Guide for the World Wide Web, ZJCAI-97, pp. 770-775.
|
| |
2
|
K. Lang. NewsWeeder: Learning to Filter News, ZCML-95, pp. 33 l-339.
|
| |
3
|
Liberman, H. Letizia: An Agent that Assists Web Browsing. ZJCAZ-95, pp. 924-929.
|
| |
4
|
Mladenic, D. Personal WebWatcher: Implementation and Design, Technical Report ZJS-DP-7472, Department for Intelligent Systems, J.Stefan Institute, October, 1996.
|
| |
5
|
M. Pazzani, J. Muramatsu, and D. Billsus. Syskill & Webert: Identifying Interesting Web Sites, AAAZ-96, pp. 54-61.
|
| |
6
|
G. Salton. Developments in Automatic Text Retrieval, Science 253~974-97
|
CITED BY 29
|
|
|
|
|
Mark Claypool , Phong Le , Makoto Wased , David Brown, Implicit interest indicators, Proceedings of the 6th international conference on Intelligent user interfaces, p.33-40, January 14-17, 2001, Santa Fe, New Mexico, United States
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Ricardo Carreira , Jaime M. Crato , Daniel Gonçalves , Joaquim A. Jorge, Evaluating adaptive user profiles for news classification, Proceedings of the 9th international conference on Intelligent user interface, January 13-16, 2004, Funchal, Madeira, Portugal
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Rajiv Badi , Soonil Bae , J. Michael Moore , Konstantinos Meintanis , Anna Zacchi , Haowei Hsieh , Frank Shipman , Catherine C. Marshall, Recognizing user interest and document value from reading and organizing activities in document triage, Proceedings of the 11th international conference on Intelligent user interfaces, January 29-February 01, 2006, Sydney, Australia
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Jeffrey P. Bigham , Anna C. Cavender , Jeremy T. Brudvik , Jacob O. Wobbrock , Richard E. Lander, WebinSitu: a comparative analysis of blind and sighted browsing behavior, Proceedings of the 9th international ACM SIGACCESS conference on Computers and accessibility, October 15-17, 2007, Tempe, Arizona, USA
|
|
|
|
|
|
|
|
|
|
|