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Data mining, management and visualization in large scientific corpuses

  • Hui Wei
    ,
  • Shaopeng Wu
    ,
  • Youbing Zhao
    ,
  • Zhikun Deng
    ,
  • Nikolaos Ersotelos
    ,
  • Farzad Parvinzamir
Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Abstract

Organizing scientific papers helps efficiently derive meaningful insights of the published scientific resources, enables researchers grasp rapid technological change and hence assists new scientific discovery. In this paper, we experiment text mining and data management of scientific publications for collecting and presenting useful information to support research. For efficient data management and fast information retrieval, four data storages are employed: a semantic repository, an index and search repository, a document repository and a graph repository, taking full advantage of their features and strength. The results show that the combination of these four repositories can effectively store and index the publication data with reliability and efficiency and hence supply meaningful information to support scientific research.

Publication Information

Output type

Research Output: Chapter in Book/Report/Conference proceeding Conference contribution Peer-review

Original language

English

Pages from-to (Number of pages)

Pages 371-379

Publication milestones

  • Published - 31/12/2016

Publication status

Published - 31/12/2016

Volume

9654

Publisher

Springer, Japan, India, Australia, Germany, United States, United Arab Emirates, Austria, Switzerland, Italy, China, United Kingdom, Netherlands, Brazil, France, Singapore

ISBN (Print)

9783319402581

External Publication IDs

  • handle.net: 10547/624195
  • Scopus: 84976620721

Host publication title

E-Learning and Games 10th International Conference, Edutainment 2016, Hangzhou, China, April 14-16, 2016, Revised Selected Papers

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