Detecting Erroneous Sentences using Automatically Mined Sequential Patterns

Detecting Erroneous Sentences using Automatically Mined Sequential Patterns

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by Guihua Sun , Xiaohua Liu , Gao Cong , Ming Zhou , Zhongyang Xiong , John Lee , Chin-yew Lin

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15 - 2 self

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@MISC{Sun_detectingerroneous,
    author = {Guihua Sun and Xiaohua Liu and Gao Cong and Ming Zhou and Zhongyang Xiong and John Lee and Chin-yew Lin},
    title = {Detecting Erroneous Sentences using Automatically Mined Sequential Patterns},
    year = {}
}

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Abstract

This paper studies the problem of identifying erroneous/correct sentences. The problem has important applications, e.g., providing feedback for writers of English as a Second Language, controlling the quality of parallel bilingual sentences mined from the Web, and evaluating machine translation results. In this paper, we propose a new approach to detecting erroneous sentences by integrating pattern discovery with supervised learning models. Experimental results show that our techniques are promising. 1

Keyphrases

erroneous sentence sequential pattern parallel bilingual sentence second language supervised learning model new approach machine translation result erroneous correct sentence pattern discovery experimental result important application paper study