Paper Info
Title
Predicting when browsing context is relevant to search
Abstract
We investigate a representative case of sudden information need change of Web users. By analyzing search engine query logs, we show that the majority of queries submitted by users after browsing documents in the news domain are related to the most recently browsed document. We investigate ways of identifying whether a query is a good candidate for contextualization conditioned on the most recently browsed document by a user. We build a successful classifier for this task, which achieves 96% precision at 90% recall.
Year
DOI
Venue
2008
10.1145/1390334.1390532
SIGIR
Keywords
Field
DocType
browsing document,successful classifier,web user,representative case,news domain,good candidate,browsed document,sudden information,search engine query log,browsing context,query expansion,information need,search engine
Query optimization,Web search query,Query language,World Wide Web,Information needs,Query expansion,Information retrieval,Computer science,Sargable,Web query classification,Ranking (information retrieval)
Conference
Citations 
PageRank 
References 
8
0.64
7
Authors
2
Name
Order
Citations
PageRank
Mandar Rahurkar1313.58
silviu cucerzan288368.80