Exploring mouse movements for inferring query intent

ABSTRACT

Clickthrough on search results have been successfully used to infer user interest and preferences, but are often noisy and potentially ambiguous. We explore the potential of a complementary, more sensitive signal -mouse movements- in providing insights into the intent behind a web search query. We report preliminary results of studying user mouse movements on search result pages, with the goal of inferring user intent - in particular, to explore whether we can automatically distinguish the different query classes such as navigational vs. informational. Our preliminary exploration confirms the value of studying mouse movements for user intent inference, and suggests interesting avenues for future exploration.

REFERENCES

• 1: Eugene Agichtein , Zijian Zheng, Identifying "best bet" web search results by mining past user behavior, Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining, August 20-23, 2006, Philadelphia, PA, USA [doi>10.1145/1150402.1150526]
• 2: Richard Atterer , Monika Wnuk , Albrecht Schmidt, Knowing the user's every move: user activity tracking for website usability evaluation and implicit interaction, Proceedings of the 15th international conference on World Wide Web, May 23-26, 2006, Edinburgh, Scotland [doi>10.1145/1135777.1135811]
• 3: Florian Mueller , Andrea Lockerd, Cheese: tracking mouse movement activity on websites, a tool for user modeling, CHI '01 extended abstracts on Human factors in computing systems, March 31-April 05, 2001, Seattle, Washington [doi>10.1145/634067.634233]
• 4: K. Rodden and X. Fu. Exploring how mouse movements relate to eye movements on web search results pages. In Proc. of WISI Workshop, 2006.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Relevance feedback

General Terms:
Design, Experimentation, Performance

Keywords:
mouse movement analysis, query intent inference, user behavior modeling