发明授权
- 专利标题: Knowledge discovery from citation networks
- 专利标题(中): 引文网络的知识发现
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申请号: US13310098申请日: 2011-12-02
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公开(公告)号: US08630975B1公开(公告)日: 2014-01-14
- 发明人: Zhen Guo , Mark Zhang
- 申请人: Zhen Guo , Mark Zhang
- 申请人地址: US NY Binghamton
- 专利权人: The Research Foundation for The State University of New York
- 当前专利权人: The Research Foundation for The State University of New York
- 当前专利权人地址: US NY Binghamton
- 代理机构: Ostrolenk Faber LLP
- 代理商 Steven M. Hoffberg
- 主分类号: G06F7/00
- IPC分类号: G06F7/00 ; G06F17/30
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.