Linking Data According to Their Degree of Representativeness (DoR)

نویسندگان

  • Frédéric Blanchard
  • Amine Aït Younes
  • Michel Herbin
چکیده

This contribution addresses the problem of extracting some representative data from complex datasets and connecting them in a directed graph. First we define a degree of representativeness (DoR) inspired of the Borda voting procedure. Secondly we present a method to connect pairwise data using neighborhoods and the DoR as an objective function. We then present case studies as illustrative purposes: unsupervised grouping of binary images, analysis of co-authorships in a research team and structuration of a medical patient-oriented database

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عنوان ژورنال:
  • EAI Endorsed Trans. Indust. Netw. & Intellig. Syst.

دوره 2  شماره 

صفحات  -

تاریخ انتشار 2015