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      Embedding technique and network analysis of scientific innovations emergence in an arXiv-based concept network

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          Abstract

          Novelty is an inherent part of innovations and discoveries. Such processes may be considered as an appearance of new ideas or as an emergence of atypical connections between the existing ones. The importance of such connections hints for investigation of innovations through network or graph representation in the space of ideas. In such representation, a graph node corresponds to the relevant concept (idea), whereas an edge between two nodes means that the corresponding concepts have been used in a common context. In this study we address the question about a possibility to identify the edges between existing concepts where the innovations may emerge. To this end, we use a well-documented scientific knowledge landscape of 1.2M arXiv.org manuscripts dated starting from April 2007 and until September 2019. We extract relevant concepts for them using the ScienceWISE.info platform. Combining approaches developed in complex networks science and graph embedding, we discuss the predictability of edges (links) on the scientific knowledge landscape where the innovations may appear.

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          Author and article information

          Journal
          23 March 2020
          Article
          2003.10289
          b35b446b-9c52-4490-bd70-e8b86befcca6

          http://arxiv.org/licenses/nonexclusive-distrib/1.0/

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          Custom metadata
          6 pages, 1 figure, submitted to IEEE Third International Conference Data Stream Mining & Processing (Dsmp2020)
          cs.DL physics.soc-ph

          General physics,Information & Library science
          General physics, Information & Library science

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