@inproceedings{f15cbdf0113b43159ffb7c9a360e934e,
title = "A stepwise detection of conjunctive structures in questions using maximum entropy model",
abstract = "This paper presents a maximum entropy model approach to identifying conjuncts of conjunctive structures in questions of financial domain from on-line discussion groups. To avoid phrasal ambiguity, only features in lexical and shallow syntactic level are used. The conjunct detection problem is converted into a stepwise boundary identification task, reducing the search space of a n-word sentence from O(n2) to O(n), The best performance on the test set achieves 85.88\% recall and 96\% rejection. This approach itself is domain-independent and can be used for conjunct identification in questions universally.",
keywords = "Conjunctive structure detection, Financial domain, Maximum entropy, Question and answering",
author = "Zhang, \{Yao Yun\} and Xuan Wang and Wang, \{Xiao Long\} and Fan, \{Shi Xi\}",
year = "2007",
doi = "10.1109/ICMLC.2007.4370830",
language = "英语",
isbn = "142440973X",
series = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
pages = "3916--3921",
booktitle = "Proceedings of the Sixth International Conference on Machine Learning and Cybernetics, ICMLC 2007",
note = "6th International Conference on Machine Learning and Cybernetics, ICMLC 2007 ; Conference date: 19-08-2007 Through 22-08-2007",
}