Sciweavers

Share
SIGIR
2010
ACM

Predicting searcher frustration

11 years 3 months ago
Predicting searcher frustration
When search engine users have trouble finding information, they may become frustrated, possibly resulting in a bad experience (even if they are ultimately successful). In a user study in which participants were given difficult information seeking tasks, half of all queries submitted resulted in some degree of self-reported frustration. A third of all successful tasks involved at least one instance of frustration. By modeling searcher frustration, search engines can predict the current state of user frustration and decide when to intervene with alternative search strategies to prevent the user from becoming more frustrated, giving up, or switching to another search engine. We present several models to predict frustration using features extracted from query logs and physical sensors. We are able to predict frustration with a mean average precision of 66% from the physical sensors, and 87% from the query log features. Categories and Subject Descriptors H.3.3 [Information Search and Retr...
Henry A. Feild, James Allan, Rosie Jones
Added 16 Aug 2010
Updated 16 Aug 2010
Type Conference
Year 2010
Where SIGIR
Authors Henry A. Feild, James Allan, Rosie Jones
Comments (0)
books