All-but-the-Top: Simple and Effective Postprocessing for Word Representations
Table 12: Before-After results (x100) on the word analogy task.
['[EMPTY]', 'RAND-WALK orig.', 'RAND-WALK proc.', 'TSCCA orig.', 'TSCCA proc.']
In summary, the performance improvements on the similarity task, the concept categorization task, the analogy task, and the semantic textual similarity dataset are on average 2.23%, 2.39%, 0.11% and 0.61%, respectively. These results are a testament to the generalization capabilities of the postprocessing algorithm to other representation algorithms.