This paper presents a maximum entropy model approach to identifying conjuncts of conjunctivestructures in questions of financial domain from on-line discussion groups. To avoid phrasal ambiguity, only features in lex...
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ISBN:
(纸本)9781424409723
This paper presents a maximum entropy model approach to identifying conjuncts of conjunctivestructures 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(n(2)) 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.
This paper presents a maximum entropy model approach to identifying conjuncts of conjunctivestructures in questions of financial domain from on-line discussion *** avoid phrasal ambiguity, only features in lexical an...
详细信息
This paper presents a maximum entropy model approach to identifying conjuncts of conjunctivestructures in questions of financial domain from on-line discussion *** avoid phrasal ambiguity, only features in lexical and shallow syntactic level are *** 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% *** approach itself is domain-independent and can be used for conjunct identification in questions universally.
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