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Articles

Topic model for graph mining based on hierarchical Dirichlet process

, &
Pages 66-77 | Received 21 Oct 2018, Accepted 07 Mar 2019, Published online: 27 Mar 2019

Figures & data

Figure 1. Graphical model representation of LDA.

Figure 1. Graphical model representation of LDA.

Figure 2. Graphical model representation of GTM.

Figure 2. Graphical model representation of GTM.

Figure 3. Graphical model representation of the HDP.

Figure 3. Graphical model representation of the HDP.

Figure 4. Graphical model representation of HDP–GTM.

Figure 4. Graphical model representation of HDP–GTM.

Figure 5. Graphical model representation of the process for text classification.

Figure 5. Graphical model representation of the process for text classification.

Figure 6. The relation between threshold value of word relation and average graph density.

Figure 6. The relation between threshold value of word relation and average graph density.

Table 1. Evaluation measures.

Figure 7. Classification effect of Reuters dataset under different ρ.

Figure 7. Classification effect of Reuters dataset under different ρ.

Table 2. Classification effects of the Reuters.

Table 3. Classification effects of the 20-newsgroup.

Figure 8. Classification effect of 20-newsgroup dataset under different ρ.

Figure 8. Classification effect of 20-newsgroup dataset under different ρ.

Figure 9. Classification effect of two datasets under HDP–GTM model.

Figure 9. Classification effect of two datasets under HDP–GTM model.

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