Task-stage knowledge support: Coupling user information needs with stage identification

I. Chin Wu*, Duen-Ren Liu, Wei Hsiao Chen

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

8 Scopus citations

Abstract

Effective knowledge support in knowledge-intensive environments can place great demands on information filtering (IF) strategies. An IF system that relies on traditional information retrieval technology and user models (e.g., user profiles) is regarded as an effective approach for supporting long-term information needs. To provide a more effective knowledge support, we propose a task-stage knowledge support model that incorporates the advantages of the traditional IF model with the characteristics of each task-stage. A correlation analysis method is proposed to determine a worker's task-stage (e.g., pre-focus, focus formulation, and post-focus task stages), and an ontology-based topic discovery method is proposed to examine the variety of a worker's information needs for specific topics. Consequently, the knowledge support is achieved by coupling user information needs with task-stage identification.

Original languageEnglish
Title of host publicationProceedings of the 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005
Pages19-24
Number of pages6
DOIs
StatePublished - 1 Dec 2005
Event2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005 - Las Vegas, NV, United States
Duration: 15 Aug 200517 Aug 2005

Publication series

NameProceedings of the 2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005
Volume2005

Conference

Conference2005 IEEE International Conference on Information Reuse and Integration, IRI - 2005
Country/TerritoryUnited States
CityLas Vegas, NV
Period15/08/0517/08/05

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