| dc.contributor | 國立政治大學資訊科學系 | en_US |
| dc.creator (作者) | 劉昭麟 | zh_TW |
| dc.creator (作者) | Wu, Chia-wei ; Liu, Chao-lin | - |
| dc.date (日期) | 2003-03 | en_US |
| dc.date.accessioned | 27-May-2010 16:48:33 (UTC+8) | - |
| dc.date.available | 27-May-2010 16:48:33 (UTC+8) | - |
| dc.date.issued (上傳時間) | 27-May-2010 16:48:33 (UTC+8) | - |
| dc.identifier.uri (URI) | http://nccur.lib.nccu.edu.tw/handle/140.119/39686 | - |
| dc.description.abstract (摘要) | In this paper, we compare two methods for article summarization. The first method is mainly based on term-frequency, while the second method is based on ontology. We build an ontology database for analyzing the main topics of the article. After identifying the main topics and determining their relative significance, we rank the paragraphs based on the relevance between main topics and each individual paragraph. Depending on the ranks, we choose desired proportion of para- graphs as summary. Experimental results indicate that both methods offer similar accuracy in their selections of the paragraphs. | - |
| dc.language | en-US | en_US |
| dc.language.iso | en_US | - |
| dc.relation (關聯) | Proceedings of the ISCA Eighteenth International Conference on Computers and Their Applications | en_US |
| dc.subject (關鍵詞) | Ontology-based text summarization;business news articles | en_US |
| dc.title (題名) | Ontology-based text summarization for business news articles | en_US |
| dc.type (資料類型) | conference | en |
