Sciweavers

Share
CHI
2009
ACM

Predicting query reformulation during web searching

12 years 6 months ago
Predicting query reformulation during web searching
This paper reports results from a study in which we automatically classified the query reformulation patterns for 964,780 Web searching sessions (composed of 1,523,072 queries) in order to predict what the next query reformulation would be. We employed an n-gram modeling approach to describe the probability of searchers transitioning from one query reformulation state to another and predict their next state. We developed first, second, third, and fourth order models and evaluated each model for accuracy of prediction. Findings show that Reformulation and Assistance account for approximately 45 percent of all query reformulations. Searchers seem to seek system searching assistant early in the session or after a content change. The results of our evaluations show that the first and second order models provided the best predictability, between 28 and 40 percent overall, and higher than 70 percent for some patterns. Implications are that the ngram approach can be used for improving search...
Bernard J. Jansen, Danielle L. Booth, Amanda Spink
Added 24 Nov 2009
Updated 24 Nov 2009
Type Conference
Year 2009
Where CHI
Authors Bernard J. Jansen, Danielle L. Booth, Amanda Spink
Comments (0)
books