IR issues for digital ecosystems users
The purpose of this research is to discuss some challenges of information retrieval, especially Web information retrieval, in digital ecosystems from a user?s perspective. As a dominant search tool, search engines usually return millions of search results in a long flat list in which many or even mo...
| Main Authors: | , |
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| Format: | Conference Paper |
| Published: |
IEEE
2008
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| Subjects: | |
| Online Access: | http://hdl.handle.net/20.500.11937/18797 |
| _version_ | 1848749849205276672 |
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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 purpose of this research is to discuss some challenges of information retrieval, especially Web information retrieval, in digital ecosystems from a user?s perspective. As a dominant search tool, search engines usually return millions of search results in a long flat list in which many or even most of the results can be irrelevant. The long flat list conveys nothing about knowledge structure related to the retrieved results and personal search preferences and interests are not explored.Although some search engines try to cluster the Web results, the automatically formed titles and knowledge hierarchy is prone to mismatching the searcher?s human mental model. In digital ecosystems, while many different search tools are available, they are not integrated. To address these issues, a search framework which combines categorization, clustering, ontology, and personalization is proposed, and thus the quality of search results in digital ecosystems is expected to be boosted. |
| first_indexed | 2025-11-14T07:27:28Z |
| format | Conference Paper |
| id | curtin-20.500.11937-18797 |
| institution | Curtin University Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-14T07:27:28Z |
| publishDate | 2008 |
| publisher | IEEE |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | curtin-20.500.11937-187972017-09-13T13:46:48Z IR issues for digital ecosystems users Zhu, Dengya Dreher, Heinz personalization Web information retrieval digital ecosystems search engines clustering categorization The purpose of this research is to discuss some challenges of information retrieval, especially Web information retrieval, in digital ecosystems from a user?s perspective. As a dominant search tool, search engines usually return millions of search results in a long flat list in which many or even most of the results can be irrelevant. The long flat list conveys nothing about knowledge structure related to the retrieved results and personal search preferences and interests are not explored.Although some search engines try to cluster the Web results, the automatically formed titles and knowledge hierarchy is prone to mismatching the searcher?s human mental model. In digital ecosystems, while many different search tools are available, they are not integrated. To address these issues, a search framework which combines categorization, clustering, ontology, and personalization is proposed, and thus the quality of search results in digital ecosystems is expected to be boosted. 2008 Conference Paper http://hdl.handle.net/20.500.11937/18797 10.1109/DEST.2008.4635203 IEEE fulltext |
| spellingShingle | personalization Web information retrieval digital ecosystems search engines clustering categorization Zhu, Dengya Dreher, Heinz IR issues for digital ecosystems users |
| title | IR issues for digital ecosystems users |
| title_full | IR issues for digital ecosystems users |
| title_fullStr | IR issues for digital ecosystems users |
| title_full_unstemmed | IR issues for digital ecosystems users |
| title_short | IR issues for digital ecosystems users |
| title_sort | ir issues for digital ecosystems users |
| topic | personalization Web information retrieval digital ecosystems search engines clustering categorization |
| url | http://hdl.handle.net/20.500.11937/18797 |