Knowledge discovery from citation networks

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United States of America Patent

PATENT NO 9892367
SERIAL NO

15049975

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Abstract

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In a corpus of scientific articles such as a digital library, documents are connected by citations and one document plays two different roles in the corpus: document itself and a citation of other documents. A Bernoulli Process Topic (BPT) model is provided which models the corpus at two levels: document level and citation level. In the BPT model, each document has two different representations in the latent topic space associated with its roles. Moreover, the multi-level hierarchical structure of the citation network is captured by a generative process involving a Bernoulli process. The distribution parameters of the BPT model are estimated by a variational approximation approach.

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Patent Owner(s)

  • THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK

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Inventor(s)

Inventor Name Address # of filed Patents Total Citations
Guo, Zhen Warrington, US 59 479
Zhang, Mark Vestal, US 18 143

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