Spherical Paragraph Model
Table 2: Classification accuracies (%) of different models on sentiment analysis.
['Model', 'Subj', 'MR']
We have the following observations: (1) SPM can outperform all the baseline methods on the Subj dataset. This indicates that SPM can capture better semantic representations of texts using a probabilistic generative model over BoWE. (2) SPM can also outperform all the baseline methods except uni-skip on the MR dataset. Note that skip-thought uses 2400-dimension sentence representation while SPM only uses 50-dimension vector. However, SPM can still achieve similar performance as uni-skip on the MR dataset even with much less model parameters.