Mining knowledge flow for modeling the information needs of task-based groups

Chin Hui Lai*, Duen-Ren Liu

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Knowledge is the most important resource to create core competitive advantages for an organization. Such knowledge is circulated and accumulated by a knowledge flow (KF) in an organization to support worker's tasks. Workers may cooperate and participate in several task-based groups to fulfill their needs. In this paper, we propose a group-based knowledge flow mining algorithm which integrates information retrieval and data mining techniques for mining and constructing the group-based KF (GKF) for task-based groups. The GKF is expressed as a directed knowledge graph to represent the knowledge referencing behavior for a group of workers with similar task needs. The frequent knowledge referencing paths are identified from the knowledge graph to indicate the frequent knowledge flows of the workers. We also implement a prototype of GKF mining system to demonstrate the effectiveness of our proposed method.

Original languageEnglish
Title of host publication2008 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2008
Pages64-69
Number of pages6
DOIs
StatePublished - 23 Sep 2008
Event2008 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2008 - Las Vegas, NV, United States
Duration: 13 Jul 200815 Jul 2008

Publication series

Name2008 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2008

Conference

Conference2008 IEEE International Conference on Information Reuse and Integration, IEEE IRI-2008
CountryUnited States
CityLas Vegas, NV
Period13/07/0815/07/08

Keywords

  • Data mining
  • Knowledge flow
  • Knowledge management
  • Process mining

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