PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks
Table 4: Results of text classification on short documents.
['Type', 'Algorithm', 'DBLP Micro-F1', 'DBLP Macro-F1', 'MR Micro-F1', 'MR Macro-F1', 'Twitter Micro-F1', 'Twitter Macro-F1']
Among unsupervised embeddings, the LINE(Gww+Gwd), which combines the document-level and local context-level word co-occurrences, performs the best. The LINE(Gww) utilizing the local context-level word co-occurrences outperforms the LINE(Gwd) using document-level word co-occurrences, which is opposite to the observations on long documents. The performance of PVDM is still inferior to that of PVDBOW, which is consistent with the results on long documents.