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Author Su, Ranxu ♦ Shang, Sheng ♦ Wang, Pan ♦ Liu, Haixu ♦ Zheng, Yan
Source CiteSeerX
Content type Text
File Format PDF
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Ntcir-9 Rite Task ♦ Zswsl Text Entailment Recognizing System ♦ Ntcir-9 Rite ♦ Classification Model ♦ Bc Subtask ♦ Chinese Textual Entailment ♦ Data Set ♦ Mc Subtask ♦ Rite Task ♦ Rule-based Algorithm ♦ Classification Task ♦ Semantic Feature ♦ Nlp Method
Abstract This paper describes our system on simplified Chinese textual entailment recognizing RITE task at NTCIR-9. Both lexical and semantic features are extracted using NLP methods. Three classification models are used and compared for the classification task, Rule-based algorithms, SVM and C4.5. C4.5 gives the best result on testing data set. Evaluation at NTCIR-9 RITE shows 72 % accuracy on BC subtask and 61.9 % accuracy on MC subtask.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article