A mouse-trajectory based model for predicting query-url relevance

Hengjie Song*, Ruoxue Liao, Xiangliang Zhang, Chunyan Miao, Qiang Yang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

6 Scopus citations

Abstract

For the learning to ranking algorithms used in commercial search engines, a conventional way to generate the training examples is to employ professional annotators to label the relevance of query url pairs. Since label quality depends on the expertise of annotators to a large extent, this process is time consuming and labor intensive. Automatically generating labels from click through data has been well studied to have comparable or better performance than human judges. Click through data present users' action and imply their satisfaction on search results, but exclude the interactions between users and search results beyond the page view level (e.g., eye and mouse movements). This paper proposes a novel approach to comprehensively consider the information underlying mouse trajectory and click through data so as to describe user behaviors more objectively and achieve a better understanding of the user experience. By integrating multi sources data, the proposed approach reveals that the relevance labels of query url pairs are related to positions of urls and users' behavioral features. Based on their correlations, query url pairs can be labeled more accurately and search results are more satisfactory to users. The experiments that are conducted on the most popular Chinese commercial search engine (Baidu) validated the rationality of our research motivation and proved that the proposed approach outperformed the state of the art methods.

Original languageEnglish (US)
Title of host publicationAAAI-12 / IAAI-12 - Proceedings of the 26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference
Pages143-149
Number of pages7
StatePublished - Nov 7 2012
Event26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12 - Toronto, ON, Canada
Duration: Jul 22 2012Jul 26 2012

Publication series

NameProceedings of the National Conference on Artificial Intelligence
Volume1

Other

Other26th AAAI Conference on Artificial Intelligence and the 24th Innovative Applications of Artificial Intelligence Conference, AAAI-12 / IAAI-12
CountryCanada
CityToronto, ON
Period07/22/1207/26/12

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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