Latent Tree Models for Hierarchical Topic Detection
Table 9: Average compactness scores.
['[EMPTY]', 'NIPS-1k', 'NIPS-5k', 'NIPS-10k', 'News-1k', 'News-5k', 'NYT']
For LDA-based methods, we reported their scores on both datasets of binary and bags-of-words versions. There is no distinct advantage of choosing either version. We see that the scores for the topics produced by HLTA are significantly higher than the those obtained by other methods in all cases.