Deep Learning for Answering Questions

Human language is still elusive for machines to comprehend. In recent years, there are much effort in pushing the performance of machines in complex tasks such as dialog and question answering. In this talk, we will review recent progress of deep recurrent neural networks in answering factoid questions regarding large knowledge bases. We will give a deep dive to our CFO system. It builds upon techniques essential to success of retrieving candidate answers from a Knowledge Base given a question: including word meaning in vector space, entity mentions in an utterance, parsing user intents in queries, and linking entities and relations in a large-scale knowledge base. It can retrieve answers for questions such as “who is the creator of Harry Potter” from tens of millions of facts.