Collaborative querying using the Query Graph Visualizer
Information overload has led to a situation where users are swamped with too much information, resulting in difficulty sifting through material in search of relevant content. We address this issue from the perspective of collaborative querying, an approach that helps users formulate queries by harne...
| Main Authors: | , , |
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| Other Authors: | |
| Format: | Journal Article |
| Language: | English |
| Published: |
2010
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/91658 http://hdl.handle.net/10220/6182 |
| _version_ | 1811686911563005952 |
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| author | Goh, Dion Hoe-Lian Fu, Lin Foo, Schubert |
| author2 | Wee Kim Wee School of Communication and Information |
| author_facet | Wee Kim Wee School of Communication and Information Goh, Dion Hoe-Lian Fu, Lin Foo, Schubert |
| author_sort | Goh, Dion Hoe-Lian |
| collection | NTU |
| description | Information overload has led to a situation where users are swamped with too much information, resulting in difficulty sifting through material in search of relevant content. We address this issue from the perspective of collaborative querying, an approach that helps users formulate queries by harnessing the collective knowledge of other searchers. We describe the design and implementation of the Query Graph Visualizer (QGV), a collaborative querying system which harvests and clusters previously issued queries to form query networks that represent related information needs. The queries in the network are explored in the QGV, helping users locate other queries that might meet their current information needs. A preliminary evaluation of the QGV is also described and results suggest the usefulness and
usability of the system. |
| first_indexed | 2024-10-01T05:07:56Z |
| format | Journal Article |
| id | ntu-10356/91658 |
| institution | Nanyang Technological University |
| language | English |
| last_indexed | 2024-10-01T05:07:56Z |
| publishDate | 2010 |
| record_format | dspace |
| spelling | ntu-10356/916582021-02-17T08:01:05Z Collaborative querying using the Query Graph Visualizer Goh, Dion Hoe-Lian Fu, Lin Foo, Schubert Wee Kim Wee School of Communication and Information DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Information overload has led to a situation where users are swamped with too much information, resulting in difficulty sifting through material in search of relevant content. We address this issue from the perspective of collaborative querying, an approach that helps users formulate queries by harnessing the collective knowledge of other searchers. We describe the design and implementation of the Query Graph Visualizer (QGV), a collaborative querying system which harvests and clusters previously issued queries to form query networks that represent related information needs. The queries in the network are explored in the QGV, helping users locate other queries that might meet their current information needs. A preliminary evaluation of the QGV is also described and results suggest the usefulness and usability of the system. Published version 2010-01-05T06:22:35Z 2019-12-06T18:09:44Z 2010-01-05T06:22:35Z 2019-12-06T18:09:44Z 2005 2005 Journal Article Goh, D., Fu, L., & Foo, S. (2005). Collaborative querying using the query graph visualizer. Online Information Review, 29(3), 266-282. 1468-4527 https://hdl.handle.net/10356/91658 http://hdl.handle.net/10220/6182 10.1108/14684520510607588 en Online information review Online Information Review @ copyright 2005 Emerald. The journal's website is located at http://www.emeraldinsight.com/Insight/viewContentItem.do?contentType=Article&contentId=1509086. 28 p. application/pdf |
| spellingShingle | DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval Goh, Dion Hoe-Lian Fu, Lin Foo, Schubert Collaborative querying using the Query Graph Visualizer |
| title | Collaborative querying using the Query Graph Visualizer |
| title_full | Collaborative querying using the Query Graph Visualizer |
| title_fullStr | Collaborative querying using the Query Graph Visualizer |
| title_full_unstemmed | Collaborative querying using the Query Graph Visualizer |
| title_short | Collaborative querying using the Query Graph Visualizer |
| title_sort | collaborative querying using the query graph visualizer |
| topic | DRNTU::Engineering::Computer science and engineering::Information systems::Information storage and retrieval |
| url | https://hdl.handle.net/10356/91658 http://hdl.handle.net/10220/6182 |
| work_keys_str_mv | AT gohdionhoelian collaborativequeryingusingthequerygraphvisualizer AT fulin collaborativequeryingusingthequerygraphvisualizer AT fooschubert collaborativequeryingusingthequerygraphvisualizer |