| A Statistical Approach with Syntactic and Semantic Features for Chinese Textual Entailment | |
|---|---|
| 學年 | 101 |
| 學期 | 1 |
| 發表日期 | 2012-08-08 |
| 作品名稱 | A Statistical Approach with Syntactic and Semantic Features for Chinese Textual Entailment |
| 作品名稱（其他語言） | |
| 著者 | Tu, Chun; Day, Min-yuh |
| 作品所屬單位 | 淡江大學資訊管理學系 |
| 出版者 | IEEE Press |
| 會議名稱 | IEEE International Conference on Information Reuse and Integration (IEEE IRI 2012) |
| 會議地點 | Vegas, Nevada, USA |
| 摘要 | Recognizing Textual Entailment (RTE) is a PASCAL/TAC task in which two text fragments are processed by system to determine whether the meaning of hypothesis is entailed from another text or not. In this paper, we proposed a textual entailment system using a statistical approach that integrates syntactic and semantic techniques for Recognizing Inference in Text (RITE) using the NTCIR-9 RITE task and make a comparison between semantic and syntactic features based on their differences. We thoroughly evaluate our approach using subtasks of the NTCIR-9 RITE. As a result, our system achieved 73.28% accuracy on the Chinese Binary-Class (BC) subtask with NTCIR-9 RITE. Thorough experiments with the text fragments provided by the NTCIR-9 RITE task show that the proposed approach can significantly improve system accuracy. |
| 關鍵字 | Textual Entailment;Semantic Features;Syntactic Features;Machine Learning;Support Vector Machine (SVM) |
| 語言 | en |
| 收錄於 | EI |
| 會議性質 | 國際 |
| 校內研討會地點 | |
| 研討會時間 | 20120808~20120810 |
| 通訊作者 | Day, Min-yuh |
| 國別 | USA |
| 公開徵稿 | Y |
| 出版型式 | 電子版 |
| 出處 | Proceedings of the IEEE International Conference on Information Reuse and Integration (IEEE IRI 2012), pp.59-64 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/78660 ) |
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