Page Hunt: using human computation games to improve web search

ABSTRACT

There has been a lot of work on evaluating and improving the relevance of web search engines, primarily using human relevance judgments or using clickthrough data. Both of these approaches look at the problem of learning the mapping from queries to web pages. In contrast, Page Hunt is a single-player human computation game which seeks to learn a mapping from web pages to queries. In particular, Page Hunt is used to elicit data from players about web pages that can be used to improve search. The data that we elicit from players has several applications including providing metadata for pages, providing query alterations for use in query refinement, and identifying ranking issues. The demo has features which make the game fun, while eliciting useful data.

REFERENCES

• 1: C. Quirk, C. Brockett, and W. B. Dolan. Monolingual Machine Translation for Paraphrase Generation. In Proc. Of EMNLP, Barcelona, Spain, 2004.
• 2: L. von Ahn. Games with a purpose. IEEE Computer, 39(6):92--94, 2006.
• 3: L. von Ahn and L. Dabbish. Designing games with a purpose. Communications of the ACM, 51(8):58--67, 2008.
• 4: H. Ma, R. Chandrasekar, C. Quirk, and A. Gupta. Page Hunt: Improving Search Engines Using Human Computation Games. In Proc. of SIGIR, Boston, USA, 2009.

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.m Miscellaneous

Additional Classification:
  H. Information Systems
  H.5 INFORMATION INTERFACES AND PRESENTATION (I.7)
      H.5.3 Group and Organization Interfaces

General Terms:
Design, Experimentation, Human Factors, Measurement

Keywords:
human computation games, relevance, web search