(2003)) topic model for estimating the semantic closeness of candidate terms, and explore different ways of utilizing LDA's topic information in automatic lexical chainers.
we use the GibbsLDA++ 5 framework for topic model estimation and inference, and examine the following LDA parameters: number of topics T , Dirichlet hyperparameters for documenttopic distribution α and topic-term distribution β.