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A Collaborative Requirement Mining Framework to Support OEMs

  • Conference paper
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Cooperative Design, Visualization, and Engineering (CDVE 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9320))

Abstract

With the fastidiously ever-increasing complexity of systems, the relentless, massive customisation of products and the mushrooming accumulation of legal documents (standards, policies and laws), we can observe a significant increase in requirements. We consider the tremendous volume of requirements as big data with which companies struggle to make strategic decisions early on. This paper proposes a collaborative requirement mining framework to enable the decision-makers of an Original Equipment Manufacturer (OEM) to gain insight and discover opportunities in a massive set of requirements so as to make early effective strategic decisions. The framework supports OEMs willing to uncover a subset of key requirements by distilling large unstructured and semi-structured specifications.

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Notes

  1. 1.

    An integrator is sometimes known as an acquirer, a customer, a contractor or a contracting authority.

  2. 2.

    An OEM is sometimes known as a subsystem provider, a subsystem supplier or a subcontractor.

  3. 3.

    One StRS for each system element.

  4. 4.

    Reddivari et al. [5] coined the term visual requirements analytics that is the use of visual analytics applied to requirements engineering. Visual analytics is “the science of analytical reasoning facilitated by interactive visual interfaces” [4].

  5. 5.

    http://www-03.ibm.com/software/products/fr/ratidoor.

  6. 6.

    http://www.3ds.com/products-services/enovia/products/v6/portfolio/d/collaborative-innovation/s/governance-user/p/requirements-central/.

  7. 7.

    http://www.reusecompany.com/requirements-quality-suite.

  8. 8.

    http://www.omg.org/spec/ReqIF/.

  9. 9.

    Create, Read, Update and Delete.

  10. 10.

    https://tika.apache.org/.

  11. 11.

    https://poi.apache.org/.

  12. 12.

    http://www.jdom.org/.

  13. 13.

    http://nlp.stanford.edu/software/corenlp.shtml.

  14. 14.

    http://mallet.cs.umass.edu/.

  15. 15.

    https://wordnet.princeton.edu/.

  16. 16.

    http://nlp.stanford.edu/software/stanford-dependencies.shtml.

  17. 17.

    https://lucene.apache.org/core/.

  18. 18.

    https://javaserverfaces.java.net/.

  19. 19.

    http://neo4j.com/.

  20. 20.

    http://projects.spring.io/spring-data-neo4j/.

  21. 21.

    http://d3js.org/.

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Author information

Authors and Affiliations

  1. Arts et Métiers ParisTech, LSIS, UMR CNRS 7296, Aix-en-Provence, France

    Romain Pinquié & Philippe Véron

  2. Arts et Métiers ParisTech, LCPI, Paris, France

    Frédéric Segonds

  3. Keonys, Toulouse, France

    Nicolas Croué

Authors
  1. Romain Pinquié
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  2. Philippe Véron
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  3. Frédéric Segonds
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  4. Nicolas Croué
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Corresponding author

Correspondence to Romain Pinquié .

Editor information

Editors and Affiliations

  1. University of Balearic Islands, Palma de Mallorca, Spain

    Yuhua Luo

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Pinquié, R., Véron, P., Segonds, F., Croué, N. (2015). A Collaborative Requirement Mining Framework to Support OEMs. In: Luo, Y. (eds) Cooperative Design, Visualization, and Engineering. CDVE 2015. Lecture Notes in Computer Science(), vol 9320. Springer, Cham. https://doi.org/10.1007/978-3-319-24132-6_13

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  • DOI: https://doi.org/10.1007/978-3-319-24132-6_13

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-24131-9

  • Online ISBN: 978-3-319-24132-6

  • eBook Packages: Computer ScienceComputer Science (R0)

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