Determining and satisfying search users real needs via socially constructed search concept classification
The focus of the research is to disambiguate search query by categorizing search results returned by search engines and interacting with the user to achieve query and results refinement. A novel special search-browser has been developed which combines search engine results, the Open DirectoryProject...
| Main Authors: | , |
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| Format: | Conference Paper |
| Published: |
IEEE
2007
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/19431 |
| _version_ | 1848750031944810496 |
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| author | Zhu, Dengya Dreher, Heinz |
| author_facet | Zhu, Dengya Dreher, Heinz |
| author_sort | Zhu, Dengya |
| building | Curtin Institutional Repository |
| collection | Online Access |
| description | The focus of the research is to disambiguate search query by categorizing search results returned by search engines and interacting with the user to achieve query and results refinement. A novel special search-browser has been developed which combines search engine results, the Open DirectoryProject (ODP) based lightweight ontology as navigator and classifier, and search results categorizing. Categories are formed based on the ODP as a predefined ontology and Lucene is to be employed to calculate the similarity between retrieved items of the search engine and concepts in the ODP. With theinteraction of users, the search-browser improves the quality of search results by excluding the irrelevant documents and ontologically categorizing results for user inspection. |
| first_indexed | 2025-11-14T07:30:22Z |
| format | Conference Paper |
| id | curtin-20.500.11937-19431 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:30:22Z |
| publishDate | 2007 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-194312017-09-13T15:56:52Z Determining and satisfying search users real needs via socially constructed search concept classification Zhu, Dengya Dreher, Heinz Information retrieval ontological filtering text classification Open Directory Project search engine The focus of the research is to disambiguate search query by categorizing search results returned by search engines and interacting with the user to achieve query and results refinement. A novel special search-browser has been developed which combines search engine results, the Open DirectoryProject (ODP) based lightweight ontology as navigator and classifier, and search results categorizing. Categories are formed based on the ODP as a predefined ontology and Lucene is to be employed to calculate the similarity between retrieved items of the search engine and concepts in the ODP. With theinteraction of users, the search-browser improves the quality of search results by excluding the irrelevant documents and ontologically categorizing results for user inspection. 2007 Conference Paper http://hdl.handle.net/20.500.11937/19431 10.1109/DEST.2007.372006 IEEE fulltext |
| spellingShingle | Information retrieval ontological filtering text classification Open Directory Project search engine Zhu, Dengya Dreher, Heinz Determining and satisfying search users real needs via socially constructed search concept classification |
| title | Determining and satisfying search users real needs via socially constructed search concept classification |
| title_full | Determining and satisfying search users real needs via socially constructed search concept classification |
| title_fullStr | Determining and satisfying search users real needs via socially constructed search concept classification |
| title_full_unstemmed | Determining and satisfying search users real needs via socially constructed search concept classification |
| title_short | Determining and satisfying search users real needs via socially constructed search concept classification |
| title_sort | determining and satisfying search users real needs via socially constructed search concept classification |
| topic | Information retrieval ontological filtering text classification Open Directory Project search engine |
| url | http://hdl.handle.net/20.500.11937/19431 |