| dc.contributor | 資管系 | |
| dc.creator (作者) | Lin, Ren Xiang;Yang, Heng-Li | |
| dc.creator (作者) | 楊亨利 | zh_TW |
| dc.date (日期) | 2014-06 | |
| dc.date.accessioned | 15-Jun-2015 16:08:26 (UTC+8) | - |
| dc.date.available | 15-Jun-2015 16:08:26 (UTC+8) | - |
| dc.date.issued (上傳時間) | 15-Jun-2015 16:08:26 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/75795 | - |
| dc.description.abstract (摘要) | The explosive growth of information on the Internet has created a great demand for new and powerful tools to acquire useful information. The first step to retrieve information form Chinese article is word segmentation. But there are two major segmentation problems that might affect the accuracy of word segmentation performance, ambiguity and long words. In this paper, we propose a novel character-based approach, namely, dynamic N-gram (DNG) to deal with the two above problems of word segmentation and apply it to Chinese news articles to evaluate the accuracy of N-gram. The evaluation result indicated most of the readers agreed that dynamic N-gram approach could extract meaningful keywords. Even in different news categories, the keywords extraction results still have no significant difference. The primary contribution of this approach is that dynamic N-gram helps us to extract the most meaningful keywords in different types of Chinese articles without considering the number of grams. © 2014 Springer International Publishing Switzerland. | |
| dc.format.extent | 176 bytes | - |
| dc.format.mimetype | text/html | - |
| dc.relation (關聯) | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Volume 8482 LNAI, Issue PART 2, 2014, Pages 398-406, 27th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2014; Kaohsiung; Taiwan; 3 June 2014 到 6 June 2014; 代碼 107164 | |
| dc.subject (關鍵詞) | Information retrieval; Intelligent systems; Chinese word segmentation; Evaluation results; Explosive growth; Keywords extraction; News articles; Primary contribution; Word segmentation; Computational linguistics | |
| dc.title (題名) | Apply the dynamic N-gram to extract the keywords of Chinese news | |
| dc.type (資料類型) | conference | en |
| dc.identifier.doi (DOI) | 10.1007/978-3-319-07467-2-42 | |
| dc.doi.uri (DOI) | http://dx.doi.org/10.1007/978-3-319-07467-2-42 | |
