Learning Semantic Textual Similarity from Conversations
Table 6: Mean Average Precision (MAP) of the proposed models on CQA subtask B.
['[EMPTY]', 'MAP']
Similar to the STS experiments, we use cosine similarity between the original question and related question, without considering any interaction between the two questions, or any contextual features. Given a related question Qi and its original question Q, we first encode them into vectors ui and u. Then the related questions are ranked based on the cosine similarity cos(ui,u) with respect to the original question. SimBow Charlet and Damnati Without any tuning on the training data provided by the task, both models show competitive performance. Reddit+SNLI model outperforms SimBow-primary, which is ranked first in the official ranking of the 2017 task.