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Concept Indexing

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Association for Computing Machinery

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Marking text in a document is a convenient way of identifying bits of knowledge that are relevant for the reader, a colleague or a larger group. Based on such markings, networks of concepts with hyperlinks to their occurrences in a collection of documents can be developed. On the Internet, marked documents can easily be shared, concepts can be constructed collaboratively and the concept-document network can be used for navigation and direct access. Text marking, grounded concepts and the Internet as base technology are characteristics of our tool for managing so called “concept indexes”. We describe the current and the new design and outline some application scenarios: electronic help desks, information digests on the Web, teaching design in virtual classes and planning under quality control in distributed teams.

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Voss, Angi; Nakata, Keiichi; Juhnke, Marcus (1999): Concept Indexing. Proceedings of the 1999 ACM International Conference on Supporting Group Work. DOI: 10.1145/320297.320298. New York, NY, USA: Association for Computing Machinery. pp. 1–10. Phoenix, Arizona, USA

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text marking, concepts, collaboration, knowledge management, documents, software agents

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Number of citations to item: 5

  • Tessai Hayama, Takashi Kanai, Susumu Kunifuji (2004): Document Skimming Support Environment for Surveying Documents in Creative Activities: Towards Supporting Environment for Creative Research Activities, In: Transactions of the Japanese Society for Artificial Intelligence, doi:10.1527/tjsai.19.113
  • Tessai Hayama, Takashi Kanai, Susumu Kunifuji (2003): Personalized Environment for Skimming Documents, In: Lecture Notes in Computer Science, doi:10.1007/978-3-540-45226-3_105
  • Grega Jakus, Veljko Milutinović, Sanida Omerović, Sašo Tomažič (2013): Concepts, In: SpringerBriefs in Computer Science, doi:10.1007/978-1-4614-7822-5_2
  • Wan Amal bt Wan Zaaimuddin, Gerald Guan Gan Goh, Uchenna C. Eze (2009): Knowledge management process and new product development performance in a Malaysian research and development organisation, In: 2009 IEEE International Conference on Industrial Engineering and Engineering Management, doi:10.1109/ieem.2009.5373522
  • (2007): Data Mining for Individual Consumer Models and Personalized Retail Promotions, In: Data Mining Methods and Applications, doi:10.1201/b15783-18
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