Revisit Semantic Representation and Tree Search for Similar Question Retrieval

This paper studies the performances of BERT in short sentence ranking task. We fine-tune BERT on the training data to get semantic vector on the test data. Given a sentence as query, we leverage k-d tree to search in all the sentence embeddings. We do the experiments on the Quora Question Pairs Dataset and process the dataset for sentence ranking. Experimental results show that our methods outperform the strong baseline. The k-d tree accelerate the speed by 50% in our experiments without losing the ranking accuracy.