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...

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Main Authors: Zhu, Dengya, Dreher, Heinz
Format: Conference Paper
Published: IEEE 2008
Subjects:
Online Access:http://hdl.handle.net/20.500.11937/18797
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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
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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