发明名称 Knowledge discovery from citation networks
摘要 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.
申请公布号 US8630975(B1) 申请公布日期 2014.01.14
申请号 US201113310098 申请日期 2011.12.02
申请人 GUO ZHEN;ZHANG MARK;THE RESEARCH FOUNDATION FOR THE STATE UNIVERSITY OF NEW YORK 发明人 GUO ZHEN;ZHANG MARK
分类号 G06F7/00;G06F17/30 主分类号 G06F7/00
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