Automatically generating effective search queries directly from community question-answering questions for finding related questions

摘要

Community Question-Answering platforms are massive knowledge bases of questions and answers pairs produced by their members. In other to provide a vibrant service, they are compelled to provide answers to new posted questions as soon as possible. However, since their dynamic requires their own users to answer questions, there is an inherent delay between posting time and the arrival of good answers. In fact, many of these new questions might be already asked and satisfactorily answered in the past. Ergo, one of the pressing needs of these services is capitalizing on good answers given to related resolved questions across their large-scale knowledge base. To that end, current approaches have studied the effectiveness of human-generated web queries across search logs in fetching related questions and potential good answers from these community archives. However, this kind of strategy is not suitable for questions without click-through data, in particular those recently posted, limiting their capability of providing them with real-time answers.