An Algorithm to Use Feedback on Viewed Documents to Improve Web Query

Patro, Sunanda; Malhotra, Vishv; Johnson, David

doi:10.1007/978-3-540-74063-6_14

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2008

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“…The user tags queries within a given text, and feature extraction and clustering are used to expand the marked queries. A similar idea is presented in [9]. First, the web results for the input query are retrieved.…”

Section: Related Workmentioning

confidence: 99%

Aquam

Menemenis

Papadopoulos

Bratu

et al. 2008

Proceedings of the 7th International Conference on Mobile and Ubiquitous Multimedia

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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.

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Section: Related Workmentioning

confidence: 99%