Open Domain Real Time Question Answering Based on Semantic and Syntactic Question Similarity
In this paper, we describe our system and results of our participation in the Live QA track of the Text Retrieval Conference(TREC) 2016. The Live QA task involves real user questions, extracted from the stream of most recent questions submitted to the Yahoo Answers (YA) site, which have not yet been answered by humans. These questions are pushed to the participants via a socket connection, and the systems are needed to provide an answer which is less than 1000 characters length in less than 60 seconds. The answers given by the system are evaluated by human experts in terms of accuracy, readability, and preciseness. Our strategy for answering the questions include question decomposition, question relatedness identification, and answer generation. Evaluation results demonstrate that our system performed close to the average scores in question answering task. In the question focus generation task our system ranked fourth.
TREC