Nonfactoid question answering (QA) is one of the most extensive yet challenging
applications and research areas in natural language processing (NLP). Existing methods fall …

Recently, Product Question Answering (PQA) on E-Commerce platforms has attracted
increasing attention as it can act as an intelligent online shopping assistant and improve the …

Product-related question answering (QA) is an important but challenging task in E-
Commerce. It leads to a great demand on automatic review-driven QA, which aims at …

Question-driven summarization has been recently studied as an effective approach to
summarizing the source document to produce concise but informative answers for non …

Response selection is a critical issue in the AI community, with important applications on the
Web. The accuracy of the selected responses, however, tends to be insufficient due to the …

Machine reading comprehension methods that generate answers by referring to multiple
passages for a question have gained much attention in AI and NLP communities. The …

Despite the impressive success of sequence to sequence models for generative question
answering, they need a vast amount of question-answer pairs during training, which is hard …

Deep learning methods that extract answers for non-factoid questions from QA sites are
seen as critical since they can assist users in reaching their next decisions through …

抄録 人間同士のコミュニケーションにおいてノンバーバル情報は, 時に言語以上に重要な役割を
持つ. なぜならば, ノンバーバル情報は人が発する言語の上に補足的な感情情報を与えるからで …

抄録 This paper tackles the goal of conclusion-supplement answer generation for non-
factoid questions, which is a critical issue in the field of Natural Language Processing (NLP) …