Aggregated click-through data in a homogeneous user community

ABSTRACT

There are many proposed methods for using clickthrough data for common queries to improve the quality of search results returned for that query. In this study we examine the search behaviour of users in a close-knit community on such queries. We argue that the benefit of using aggregated clickthrough data varies from task to task: it may improve document rankings for navigational or specific informational queries, but is less likely to be of value to users issuing a broad informational query.

REFERENCES

• 1: Mingfang Wu , Andrew Turpin , Justin Zobel, An investigation on a community's web search variability, Proceedings of the thirty-first Australasian conference on Computer science, January 01-01, 2008, Wollongong, Australia
• 2: Eugene Agichtein , Eric Brill , Susan Dumais, Improving web search ranking by incorporating user behavior information, Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval, August 06-11, 2006, Seattle, Washington, USA [doi>10.1145/1148170.1148177]
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INDEX TERMS

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

General Terms:
Experimentation, Human Factors, Reliability

Keywords:
information need, query logs, search variability