Mining and Supporting Task-Stage Knowledge: A Hierarchical Clustering Technique

  • Duen-Ren Liu
  • I-Chin Wu
  • Wei-Hsiao Chen
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4333)


In task-based business environments, organizations usually conduct knowledge-intensive tasks to achieve organizational goals; thus, knowledge management systems (KMSs) need to provide relevant information to fulfill the information needs of knowledge workers. Since knowledge workers usually accomplish a task in stages, their task-needs may be different at various stages of the task’s execution. Thus, an important issue is how to extract knowledge from historical tasks and further support task-relevant knowledge according to the workers’ task-needs at different task-stages. This work proposes a task-stage mining technique for discovering task-stage needs from historical (previously executed) tasks. The proposed method uses information retrieval techniques and a modified hierarchical agglomerative clustering algorithm to identify task-stage needs by analyzing codified knowledge (documents) accessed or generated during the task’s performance. Task-stage profiles are generated to model workers’ task-stage needs and used to deliver task-relevant knowledge at various task-stages. Finally, we conduct empirical evaluations to demonstrate that the proposed method provides a basis for effective knowledge support.


knowledge-intensive task task-relevant knowledge task-stage mining hierarchical agglomerative clustering 


Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.


  1. 1.
    Abecker, A., Bernardi, A., Maus, H., Sintek, M., Wenzel, C.: Information Supply for Business Processes: Coupling Workflow with Document Analysis and Information Retrieval. Knowledge Based Systems 13(1), 271–284 (2000)CrossRefGoogle Scholar
  2. 2.
    Baeza-Yates, R., Ribeiro-Neto, B.: Modern Information Retrieval. ACM Press, New York (1999)Google Scholar
  3. 3.
    Bolloju, N., Khalifa, M., Turban, E.: Integrating Knowledge Management into Enterprise Environments for the Next Generation Decision Support. Decision Support Systems 33(22), 163–176 (2002)CrossRefGoogle Scholar
  4. 4.
    Chuang, S.-L., Chien, L.-F.: A Practical Web-based Approach to Generating Topic Hierarchy for Text Segments. In: CIKM, pp. 127–136 (2004)Google Scholar
  5. 5.
    Davenport, T.H., Prusak, L.: Working knowledge: How Organizations Manages What They Know. Harvard Business School Press, Boston (1998)Google Scholar
  6. 6.
    Fenstermacher, K.D.: Process-Aware Knowledge Retrieval. In: Proc. of the 35th Hawaii Intl. Conf. on System Sciences, Hawaii, USA, pp. 209–217 (2002)Google Scholar
  7. 7.
    Jain, A.K., Murty, M.N., Flynn, P.J.: Data Clustering: A Review. ACM Computing Surveys 31(3), 264–323 (1999)CrossRefGoogle Scholar
  8. 8.
    Johnson, S.C.: Hierarchical Clustering Schemes. Psychometrika 2, 241–254 (1967)CrossRefGoogle Scholar
  9. 9.
    Kuhlthau, C.: Seeking Meaning: A Process Approach to Library and Information Services. Ablex Publishing Corp., Norwood (1993)Google Scholar
  10. 10.
    Liu, D.-R., Wu, I.-C., Yang, K.-S.: Task-based K-Support System: Disseminating and Sharing Task-relevant Knowledge. Expert Systems with Applications 29(2), 408–423 (2005)CrossRefGoogle Scholar
  11. 11.
    Markus, M.L.: Toward a Theory of Knowledge Reuse: Types of Knowledge Reuse Situation and Factors in Reuse Success. Journal of Management Information Systems 18(1), 57–94 (2001)MathSciNetGoogle Scholar
  12. 12.
    van Rijsbergen, C.J.: Information Retrieval, 2nd edn. Butterworths, London (1979)Google Scholar
  13. 13.
    Riloff, E., Lehnert, W.: Information Extraction as a Basis for High Precision Text Classification. ACM Transaction on Information System 12(3), 296–333 (1994)CrossRefGoogle Scholar
  14. 14.
    Vakkari, P.: Cognition and Changes of Search Terms and Tactics during Task Performance: A Longitudinal Case Study. In: Proceedings of the RIAO 2000 Conference, C.I.D, Paris, pp. 894–907 (2000)Google Scholar
  15. 15.
    Wu, I.-C., Liu, D.-R., Chen, W.-H.: Task-stage Knowledge Support Model: Coupling User Information Needs with Stage Identification. In: Proc. of the IEEE 2005 Intl. Conf. on Information Reuse and Integration (IRI), Las Vegas, USA (2005)Google Scholar
  16. 16.
    Zack, M.H.: Managing Codified Knowledge. Sloan Management Review 40(4), 45–58 (1999)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Duen-Ren Liu
    • 1
  • I-Chin Wu
    • 2
  • Wei-Hsiao Chen
    • 1
  1. 1.Institute of Information ManagementNational Chiao Tung UniversityTaiwan
  2. 2.Department of Information ManagementFu Jen Catholic UniversityTaiwan

Personalised recommendations