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Building Content-driven Entity Networks for Scarce Scientific Literature using Content Information
International Conference on Computational Linguistics
This paper proposes several network construction methods for collections of scarce scientific literature data. We define scarcity as lacking in value and in volume. Instead of using the paper's metadata to construct several kinds of scientific networks, we use the full texts of the articles and automatically extract the entities needed to construct the networks. Specifically, we present seven kinds of networks using the proposed construction methods: co-occurrence networks for author, keyword,dblp:conf/coling/AmplayoS16 fatcat:d7qfurx3efef7mb3aotxp3lzni