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Analyzing Website Content for Improved R&T Collaboration Planning

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Advances in Information Systems and Technologies

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 206))

Abstract

A well-known problem in research and technology (R&T) planning is the selection of suited R&T collaboration partners. We investigate the use of textual information from the website content of possible collaboration candidates to identify their suitability. This improves the selection of collaboration partners and it enables a successful processing of R&T-projects. In a case study ‘defense R&T’, organizations and companies that have proven their suitability as collaboration partner in former R&T projects are selected (positive examples) as well as organizations and companies that have not. Latent semantic indexing with singular value decomposition and logistic regression modeling is used to identify semantic textual patterns from their websites’ content. As a result of prediction modeling, some of these textual patterns are successful in predicting new organizations or companies as (un-) suited R&T collaboration partners. These results support the acquisition of new collaboration partners and thus, they are valuable for the planning of R&T.

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Author information

Authors and Affiliations

  1. Fraunhofer INT, Appelsgarten 2, D-53879, Euskirchen, Germany

    Dirk Thorleuchter

  2. Faculty of Economics and Business Administration, Ghent University, Tweekerkenstraat 2, B-9000, Gent, Belgium

    Dirk Van den Poel

Authors
  1. Dirk Thorleuchter
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  2. Dirk Van den Poel
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Correspondence to Dirk Thorleuchter .

Editor information

Editors and Affiliations

  1. , Faculty of Science and Technology, University Fernando Pessoa, Praça 9 de Abril 349, Porto, 4249-004, Portugal

    Álvaro Rocha

  2. , Instituto Superior de Estatística e, Universidade Nova de Lisboa, Campus de Campolide, Lisboa, 1070-312, Portugal

    Ana Maria Correia

  3. Broomfield Road 9, Sheffield, S10 2SE, United Kingdom

    Tom Wilson

  4. Empirica GmbH, Oxfordstr. 2, Bonn, 53111, Germany

    Karl A. Stroetmann

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Thorleuchter, D., Van den Poel, D. (2013). Analyzing Website Content for Improved R&T Collaboration Planning. In: Rocha, Á., Correia, A., Wilson, T., Stroetmann, K. (eds) Advances in Information Systems and Technologies. Advances in Intelligent Systems and Computing, vol 206. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-36981-0_52

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  • DOI: https://doi.org/10.1007/978-3-642-36981-0_52

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-36980-3

  • Online ISBN: 978-3-642-36981-0

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