An algorithm for suffix stripping
Readings in information retrieval
Placing search in context: the concept revisited
Proceedings of the 10th international conference on World Wide Web
Automatic query wefinement using lexical affinities with maximal information gain
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
WWW '03 Proceedings of the 12th international conference on World Wide Web
Improving Category Specific Web Search by Learning Query Modifications
SAINT '01 Proceedings of the 2001 Symposium on Applications and the Internet (SAINT 2001)
Query Expansion by Mining User Logs
IEEE Transactions on Knowledge and Data Engineering
Introduction to Data Mining, (First Edition)
Introduction to Data Mining, (First Edition)
Proceedings of the 15th international conference on World Wide Web
Deciphering mobile search patterns: a study of Yahoo! mobile search queries
Proceedings of the 17th international conference on World Wide Web
Simrank++: query rewriting through link analysis of the clickgraph (poster)
Proceedings of the 17th international conference on World Wide Web
First query term extraction from current webpage for mobile applications
Proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia
Discovery of environmental nodes in the web
IRFC'12 Proceedings of the 5th conference on Multidisciplinary Information Retrieval
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When a user performs a web search, the first query entered will frequently not return the required information. Thus, one needs to review the initial set of links and then to modify the query or construct a new one. This incremental process is particularly frustrating and difficult to manage for a mobile user due to the device limitations (e.g. keyboard, display). We present a query formulation architecture that employs the notion of context in order to automatically construct queries, where context refers to the article currently being viewed by the user. The proposed system uses semantic metadata extracted from the web page being consumed to automatically generate candidate queries. Novel methods are proposed to create and validate candidate queries. Further two variants of query expansion and a post-expansion validation technique are described. Finally, insights into the effectiveness of our system are provided based on evaluation tests of its individual components.