UH-PRHLT at SemEval-2016 Task 3:Combining Lexical and Semantic-based Features forCommunity Question Answering
Table 2: Results of Subtask B: English Question-Question Similarity. (a) Baselines; (b) proposed approach.
['[EMPTY]', '[BOLD] Model', '[BOLD] Ranking measures  [BOLD] MAP', '[BOLD] Ranking measures  [BOLD] AvgRec', '[BOLD] Ranking measures  [BOLD] MRR', '[BOLD] Classification measures  [BOLD] Acc.', '[BOLD] Classification measures  [BOLD] P', '[BOLD] Classification measures  [BOLD] R', '[BOLD] Classification measures  [BOLD] F1']
Similar to Subtask A, the performance of our approach has been also superior in Subtask B (question-related question similarity ranking). In this case, the similarity between questions was easier to estimate — also for the baselines — and the improvements in performance were slightly reduced. With respect to the classification measures, we outperformed the random baseline with 27.4% and 16.1 % of accuracy and F1-measure respectively.