Abstract
The question answering (QA) task consists of providing short, relevant answers to natural language questions. Most QA research has focused on extracting information from text sources, providing the shortest relevant text in response to a question. For example, the correct answer to the question, “How many groups participate in the CHIL project?” is “15”, whereas the response to “Who are the partners in CHIL?” is a list of them. This simple example illustrates the two main advantages of QA over current search engines: First, the input is a natural-language question rather a keyword query; and second, the answer provides the desired information content and not simply a potentially large set of documents or URLs that the user must plow through.
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Turmo, J., Surdeanu, M., Galibert, O., Rosset, S. (2009). Language Technologies: Question Answering in Speech Transcripts. In: Waibel, A., Stiefelhagen, R. (eds) Computers in the Human Interaction Loop. Human–Computer Interaction Series. Springer, London. https://doi.org/10.1007/978-1-84882-054-8_8
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