Question Answering and Generation

Abstract

Automated Question Answering and Asking are two active areas of Natural Language Processing with the former dominating the past decade and the latter most likely to dominate the next one. Due to the vast amounts of information available electronically in the Internet era, automated Question Answering is needed to fulfill information needs in an efficient and effective manner. Automated Question Answering is the task of providing answers automatically to questions asked in natural language. Typically, the answers are retrieved from large collections of documents. While answering any question is difficult, successful automated solutions to answer some type of questions, so-called factoid questions, have been developed recently, culminating with the just announced Watson Question Answering system developed by I.B.M. to compete in Jeopardy-like games. The flip process, automated Question Asking or Generation, is about generating questions from some form of input such as a text, meaning representation, or database. Question Asking/Generation is an important component in the full gamut of learning technologies, from conventional computer-based training to tutoring systems. Advances in Question Asking/Generation are projected to revolutionize learning and dialogue systems. This chapter presents an overview of recent developments in Question Answering and Generation starting with the landscape of questions that people ask.