A user-oriented webpage ranking algorithm based on user attention time

Songhua Xu, Yi Zhu, Hao Jiang, Francis C.M. Lau

Research output: Chapter in Book/Report/Conference proceedingConference contribution

15 Scopus citations

Abstract

We propose a new webpage ranking algorithm which is personalized. Our idea is to rely on the attention time spent on a document by the user as the essential clue for producing the user-oriented webpage ranking. The prediction of the attention time of a new webpage is based on the attention time of other previously browsed pages by this user. To acquire the attention time of the latter webpages, we developed a browser plugin which is able to record the time a user spends reading a certain webpage and then automatically send that data to a server. Once the user attention time is acquired, we calibrate it to account for potential repetitive occurrences of the webpage before using it in the prediction process. After the user's attention times of a collection of documents are known, our algorithm can predict the user's attention time of a new document through document content similarity analysis, which is applied to both texts and images. We evaluate the webpage ranking results from our algorithm by comparing them with the ones produced by Google's Pagerank algorithm.

Original languageEnglish (US)
Title of host publicationAAAI-08/IAAI-08 Proceedings - 23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference
Pages1255-1260
Number of pages6
StatePublished - 2008
Event23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08 - Chicago, IL, United States
Duration: Jul 13 2008Jul 17 2008

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume2

Other

Other23rd AAAI Conference on Artificial Intelligence and the 20th Innovative Applications of Artificial Intelligence Conference, AAAI-08/IAAI-08
CountryUnited States
CityChicago, IL
Period7/13/087/17/08

All Science Journal Classification (ASJC) codes

  • Software
  • Artificial Intelligence

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