Using syntactic distributional patterns for data-driven answer extraction from the Web

Figueroa, A; Atkinson J.

Keywords: systems, patterns, acquisition, learning, extraction, world, pattern, principles, language, computer, data, languages, type, web, matching, wide, programming, feature, Expected, Answer, Contextual, Distributional, (EAT)


In this work, a data-driven approach for extracting answers from web-snippets is presented. Answers are identified by matching contextual distributional patterns of the expected answer type(EAT) and answer candidates. These distributional patterns are directly learnt from previously annotated tuples {question, sentence, answer}, and the learning mechanism is based on the principles language acquisition. Results shows that this linguistic motivated data-driven approach is encouraging. © Springer-Verlag Berlin Heidelberg 2006.

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Título de la Revista: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volumen: 4293
Editorial: Society of Laparoendoscopic Surgeons
Fecha de publicación: 2006
Página de inicio: 985
Página final: 995