Sentence examples for topic model from inspiring English sources

LDA is a powerful probabilistic topic model.

The topic model results are presented in Table 3.

Terminal leaves of the topic model are marked in gray.

In previous empirical studies, it shows that the character-based topic model performs better than the word-based topic model.

The experimental results reveal that our ontology-based topic model method outperforms a traditional topic model method.

One such simple extension is the Correlated Topic Model (CTM) [14].

It employs the PLSA modeling technique (described in Section 4) to build the topic model.

Table 4 lists the parameters used for the LDA topic model.

Topic model results were analysed manually by inspecting the top relevant words (i.e., 20 per topic).

Terminal leaf nodes of the tree are chosen to represent the flat topic model.

In this research, the LDA topic model was employed to extract opinions from user reviews.