Infinite Coauthor Topic Model (Infinite coAT): A Non-Parametric Generalization for coAT Model
نویسندگان
چکیده
Inspired by the hierarchical Dirichlet process (HDP), we present a generalized coAT (coauthor Topic) model, also called infinite coAT model, in this paper. The infinite coAT model is a nonparametric extension of the coAT model. And this model can automatically determine the number of topics which are regarded for the probabilistic distribution of words. One does not need to provide prior information about the number of topics. In order to keep the consistency with the coAT model, the Gibbs sampling is utilized to infer the parameters. Finally, experimental results on the US patents dataset from US Patent Office indicate that our infinite-coAT model is feasible and efficient.
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