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How to Extract Knowledge from Professional E-Mails

Author

Listed:
  • François Rauscher

    (Tech-CICO - TECHnologies pour la Coopération, l’Interaction et les COnnaissances dans les collectifs - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique - CNRS - Centre National de la Recherche Scientifique)

  • Nada Matta

    (Tech-CICO - TECHnologies pour la Coopération, l’Interaction et les COnnaissances dans les collectifs - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique - CNRS - Centre National de la Recherche Scientifique)

  • Hassan Atifi

    (Tech-CICO - TECHnologies pour la Coopération, l’Interaction et les COnnaissances dans les collectifs - ICD - Institut Charles Delaunay - UTT - Université de Technologie de Troyes - CNRS - Centre National de la Recherche Scientifique - CNRS - Centre National de la Recherche Scientifique)

Abstract

Computer mediated communication is ubiquitous in Software design projects. Email is used for project coordination, but also for design, implementation and test. Especially with currents agile development methods, it is very common to interact through computer meditated communication like email, instant messaging and other collaborative tools in order to express functional needs, notify of issues and take appropriate decisions. In this paper we propose a Knowledge Trace Retrieval (KTR) system. It addresses the problem of retrieving elements of problem solving and design rationale inside business emails from a project. Even if knowledge management tools and practices are well spread in industry, they are rarely used for small projects. Our system aims at helping user retrieve traces of problem solving knowledge in large corpus of email from a past project. The framework and methodology is based on enhanced context (project data, user competencies and profiles), and use machine learning technics and ranking algorithm.

Suggested Citation

  • François Rauscher & Nada Matta & Hassan Atifi, 2015. "How to Extract Knowledge from Professional E-Mails," Post-Print hal-02918398, HAL.
    • Handle: RePEc:hal:journl:hal-02918398
    DOI: 10.1109/SITIS.2015.113
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