@inproceedings{96fda6986d3e44d5889796b31df911e8,
title = "Using syntactic distributional patterns for data-driven answer extraction from the Web",
abstract = "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.",
keywords = "Natural language processing, Question answering",
author = "Alejandro Figueroa and John Atkinson",
year = "2006",
doi = "10.1007/11925231_94",
language = "English",
isbn = "3540490264",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Verlag",
pages = "985--995",
booktitle = "MICAI 2006",
note = "5th Mexican International Conference on Artificial Intelligence, MICAI 2006: Advances in Artificial Intelligence ; Conference date: 13-11-2006 Through 17-11-2006",
}