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Generating rules from data mining for collaboration moderator services

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Abstract

A Moderator is a knowledge based system that supports collaborative working by raising awareness of the priorities and requirements of other team members. However, the amount of advice a Moderator can provide is limited by the knowledge it contains on team members. The use of data mining techniques can contribute towards automating the process of knowledge acquisition for a Moderator and enable hidden data patterns and relationships to be discovered to facilitate the moderation process. A novel approach is presented, consisting of a knowledge discovery framework which provides a semi-automatic methodology to generate rules by inserting relationships discovered as a result of data mining into a generic template. To demonstrate the knowledge discovery framework methodology an application case is described. The application case acquires knowledge for a Moderator to make project partners aware of how to best formulate a proposal for a European research project by data mining summaries of successful past projects. Findings from the application case are presented.

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Authors and Affiliations

  1. Wolfson School of Mechanical and Manufacturing Engineering, Loughborough University, Leicestershire, LE11 3TU, UK

    C. Palmer, J. A. Harding, R. Swarnkar, B. P. Das & R. I. M. Young

Authors
  1. C. Palmer
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  2. J. A. Harding
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  3. R. Swarnkar
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  4. B. P. Das
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  5. R. I. M. Young
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Correspondence to J. A. Harding.

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Palmer, C., Harding, J.A., Swarnkar, R. et al. Generating rules from data mining for collaboration moderator services. J Intell Manuf 24, 313–330 (2013). https://doi.org/10.1007/s10845-011-0589-2

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  • DOI: https://doi.org/10.1007/s10845-011-0589-2

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