| dc.contributor | 資訊管理系 | zh_Tw |
| dc.creator (作者) | 謝宇倫 | zh_TW |
| dc.creator (作者) | Chang, Yung-Chun | en_US |
| dc.creator (作者) | Chen, Cen-Chieh | en_US |
| dc.creator (作者) | Hsieh, Yu-Lun | en_US |
| dc.creator (作者) | Chen, Chien Chin | en_US |
| dc.creator (作者) | Hsu, Wen-Lian | en_US |
| dc.date (日期) | 2015-07 | en_US |
| dc.date.accessioned | 14-八月-2017 15:33:59 (UTC+8) | - |
| dc.date.available | 14-八月-2017 15:33:59 (UTC+8) | - |
| dc.date.issued (上傳時間) | 14-八月-2017 15:33:59 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/111934 | - |
| dc.description.abstract (摘要) | In this paper, we propose a flexible principle-based approach (PBA) for reader-emotion classification and writing assistance. PBA is a highly automated process that learns emotion templates from raw texts to characterize an emotion and is comprehensible for humans. These templates are adopted to predict reader-emotion, and may further assist in emotional resonance writing. Results demonstrate that PBA can effectively detect reader-emotions by exploiting the syntactic structures and semantic associations in the context, thus outperforming wellknown statistical text classification methods and the state-of-the-art reader-emotion classification method. Moreover, writers are able to create more emotional resonance in articles under the assistance of the generated emotion templates. These templates have been proven to be highly interpretable, which is an attribute that is difficult to accomplish in traditional statistical methods. © 2015 Association for Computational Linguistics. | en_US |
| dc.format.extent | 331478 bytes | - |
| dc.format.mimetype | application/pdf | - |
| dc.relation (關聯) | ACL-IJCNLP 2015 - 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, Proceedings of the Conference, 2(), 775-780 | en_US |
| dc.relation (關聯) | 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing of the Asian Federation of Natural Language Processing, ACL-IJCNLP 2015; Beijing; China; 26 July 2015 到 31 July 2015; 代碼 114195 | zh_TW |
| dc.subject (關鍵詞) | Automation; Classification (of information); Computational linguistics; Linguistics; Resonance; Semantics; Syntactics; Text processing; Automated process; Emotion classification; Semantic associations; State of the art; Syntactic structure; Template extraction; Text classification methods; Natural language processing systems | en_US |
| dc.title (題名) | Linguistic template extraction for recognizing reader-emotion and emotional resonance writing assistance | en_US |
| dc.type (資料類型) | conference | |
