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Query graph visualizer: A collaborative querying system

dc.contributor.authorFu, Lin
dc.contributor.authorGoh, Dion Hoe-Lian
dc.contributor.authorFoo, Schubert Shou-Boon
dc.contributor.authorSupangat, Yohan
dc.contributor.editorDoroshenko, Anatoly E.
dc.contributor.editorHalpin, Terry A.
dc.contributor.editorLiddle, Stephen W.
dc.contributor.editorMayr, Heinrich C.
dc.date.accessioned2019-10-15T12:40:40Z
dc.date.available2019-10-15T12:40:40Z
dc.date.issued2004
dc.description.abstractCollaborative querying seeks to help users formulate an accurate query to a search engine by sharing expert knowledge or other users' search experiences. One approach to accomplish collaborative querying is to cluster related queries which are stored in query logs and use the related queries as recommendations to users. Here, the kernel step is to identify the similarity between queries. This paper describes a system that supports collaborative querying among its users. The system operates by clustering and recommending related queries to users using a hybrid query similarity identification approach. The system employs a graph approach to visualize the query recommendations.en
dc.identifier.isbn3-88579-377-6
dc.identifier.pissn1617-5468
dc.identifier.urihttps://dl.gi.de/handle/20.500.12116/29101
dc.language.isoen
dc.publisherGesellschaft für Informatik e.V.
dc.relation.ispartofInformation systems technology and its applications, 3rd international conference ISTA'2004
dc.relation.ispartofseriesLecture Notes in Informatics (LNI) - Proceedings, Volume P-48
dc.titleQuery graph visualizer: A collaborative querying systemen
dc.typeText/Conference Paper
gi.citation.endPage240
gi.citation.publisherPlaceBonn
gi.citation.startPage235
gi.conference.dateJune 15-17, 2004
gi.conference.locationSalt Lake City, Utah, USA
gi.conference.sessiontitleRegular Research Papers

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