A pilot study on enhancing the application of knowledge management systems using semantic segmentation

Ji Wei Wu, Judy C.R. Tseng, Wen Der Yu, Jyh Bin Yang, Wen Nung Tsai, Shun Min Lee

Research output: Contribution to conferencePaperpeer-review

Abstract

Owing to extensive knowledge management activities are promoted in various enterprises. How to enhance the application of knowledge management systems (KMS) becomes a critical issue. One of the enhanced applications of KMS is the SOS system, which aims at sharing knowledge for solving emerging problems. While it takes time for experienced employees to share their knowledge via the SOS system, it is advantageous to introduce an Automatic Problem Answering (APA) mechanism. When an emerging problem is issued, the APA mechanism will find actively suitable knowledge from the Intellectual Asset Repository (IAR), which consists of various sources of knowledge. In this paper, a semantic segmentation method is proposed and is employed in building a semantic segmentation module (SSM) in APA. SSM will automatically extract the knowledge corpuses embedded in documents. The extracted knowledge corpuses will be reused in APA to solve emergent problems and thus the application of KMS is enhanced.

Original languageEnglish
Pages578-587
Number of pages10
StatePublished - 2010
Event27th International Symposium on Automation and Robotics in Construction, ISARC 2010 - Bratislava, Slovakia
Duration: 25 Jun 201027 Jun 2010

Conference

Conference27th International Symposium on Automation and Robotics in Construction, ISARC 2010
Country/TerritorySlovakia
CityBratislava
Period25/06/1027/06/10

Keywords

  • Knowledge management
  • Semantic segmentation
  • Text mining

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