Collaborative querying for enhanced information retrieval
Communication and collaboration with other people is a major theme in the information seeking process. Collaborative querying addresses this issue by sharing other users’ search experiences to help users formulate appropriate queries to a search engine. This paper describes a collaborative querying...
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sg-ntu-dr.10356-915562020-03-07T12:15:48Z Collaborative querying for enhanced information retrieval Fu, Lin Goh, Dion Hoe-Lian Supangat, Yohan Foo, Schubert Wee Kim Wee School of Communication and Information European Conference on Digital Libraries (8th : 2004 : Bath) DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Communication and collaboration with other people is a major theme in the information seeking process. Collaborative querying addresses this issue by sharing other users’ search experiences to help users formulate appropriate queries to a search engine. This paper describes a collaborative querying system that helps users with query formulation by finding previously submitted similar queries through mining web logs. The system operates by clustering and recommending related queries to users using a hybrid query similarity identification approach. The system employs a graph-based approach to visualize the query recommendations. Published version 2010-01-04T07:09:40Z 2019-12-06T18:07:50Z 2010-01-04T07:09:40Z 2019-12-06T18:07:50Z 2004 2004 Conference Paper Fu, L., Goh, D., Foo, S., & Supangat, Y. (2004). Collaborative Querying for Enhanced Information Retrieval. Proceedings of the 8th European Conference on Digital Libraries ECDL 2004, (September 12-17, Bath, UK), Lecture Notes in Computer Science 3232, 378-388. https://hdl.handle.net/10356/91556 http://hdl.handle.net/10220/6176 10.1007/b100389 en 13 p. application/pdf |
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DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Fu, Lin Goh, Dion Hoe-Lian Supangat, Yohan Foo, Schubert Collaborative querying for enhanced information retrieval |
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Communication and collaboration with other people is a major theme in the information seeking process. Collaborative querying addresses this issue by sharing other users’ search experiences to help users formulate appropriate queries to a search engine. This paper describes a collaborative querying system that helps users with query formulation by finding previously submitted similar queries through mining web logs. The system operates by clustering and recommending related queries to users using a hybrid query similarity identification approach. The system employs a graph-based approach to visualize the query recommendations. |
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Wee Kim Wee School of Communication and Information |
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Wee Kim Wee School of Communication and Information Fu, Lin Goh, Dion Hoe-Lian Supangat, Yohan Foo, Schubert |
format |
Conference or Workshop Item |
author |
Fu, Lin Goh, Dion Hoe-Lian Supangat, Yohan Foo, Schubert |
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Fu, Lin |
title |
Collaborative querying for enhanced information retrieval |
title_short |
Collaborative querying for enhanced information retrieval |
title_full |
Collaborative querying for enhanced information retrieval |
title_fullStr |
Collaborative querying for enhanced information retrieval |
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Collaborative querying for enhanced information retrieval |
title_sort |
collaborative querying for enhanced information retrieval |
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2010 |
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https://hdl.handle.net/10356/91556 http://hdl.handle.net/10220/6176 |
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1681036905862397952 |