Page hunt: improving search engines using human computation games

There has been a lot of work on evaluating and improving the relevance of web search engines. In this paper, we suggest using human computation games to elicit data from players that can be used to improve search. We describe Page Hunt, a single-player game. The data elicited using Page Hunt has several applications including providing metadata for pages, providing query alterations for use in query refinement, and identifying ranking issues. We describe an experiment with over 340 game players, and highlight some interesting aspects of the data obtained. Categories and Subject Descriptors: H.3.m [Information Storage and Retrieval]: Miscellaneous General Terms: Design, Experimentation, Human Factors.

• Type: Conference
• Year: 2009
• Where: SIGIR
• Authors: Hao Ma, Raman Chandrasekar, Chris Quirk, Abhishek Gupta
• Keywords: Human Computation Games, Page Hunt, SIGIR 2009, Web Search Engines