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szbinlee木虫 (正式写手)
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[求助]
求论文的EI检索信息
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请帮忙查询一下该论文是否EI检索。 题目：Improving Translation of Organization Names Combining Translation Model and Web Mining 作者：Bin Li 1, Yin Zhou2, Ning Ma1, Wuqi Liang1, Lulu Dong1 期刊：International Journal of Database Theory and Application 最好能提供PDF文档。谢谢  |
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感谢参与，应助指数 +1
szbinlee: 金币+30, ★★★★★最佳答案, 非常感谢！！！ 2016-05-20 17:49:13
sunshan4379: LS-EPI+1, 感谢应助！ 2016-05-20 19:07:11
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Accession number: 20160601905693 Title: Improving translation of organization names combining translation model and web mining Authors: Li, Bin1 Email author szbinlee@126.com; Zhou, Yin2 Email author zhouyin05029@foxmail.com; Ma, Ning1 Email author Maning@ahou.edu.cn; Liang, Wuqi1 Email author Liangwuqi@ahou.edu.cn; Dong, Lulu1 Email author Donglulu@ahou.edu.cn Author affiliation: 1 Anhui Radio and Television University, No. 398, Tongcheng Road, Hefei City, Anhui Province, China 2 Hubei Engineering University, No.272, Jiaotong Road, Xiaogan City, Hubei Province, China Source title: International Journal of Database Theory and Application Abbreviated source title: Int. J. Database Theory Appl. Volume: 9 Issue: 1 Issue date: 2016 Publication year: 2016 Pages: 143-154 Language: English ISSN: 20054270 Document type: Journal article (JA) Publisher: Science and Engineering Research Support Society Abstract: Named entity (NE) translation is a fundamental task in machine translation (MT) and cross-language information retrieval (CLIR). Furthermore, Organization name (ON) translation is the most complex among all the NEs. A novel system for translating ONs from Chinese to English, with a translation model and web resources, is proposed. Firstly, we built a translation model with Chunk. Then query expansion was adopted with the translation model and term-subject co-occurrence. Thirdly, we extracted the Chinese Organization names with English sentences using the method of frequency shifting and adjacency information to find English fragments as translation candidates. Finally, we found the best translation by computing the trustworthiness of all candidates. The experimental results showed that the approach returned a better performance than machine translation-based systems. © 2016 SERSC. Number of references: 20 Main heading: Computational linguistics Controlled terms: Computer aided language translation - Data mining Uncontrolled terms: Cross-language information retrieval - English sentences - Frequency-shifting - Machine translations - Named entities - Query expansion - Translation models - Web Mining Classification code: 721.1 Computer Theory, Includes Formal Logic, Automata Theory, Switching Theory, Programming Theory - 723.2 Data Processing and Image Processing - 723.5 Computer Applications DOI: 10.14257/ijdta.2016.9.1.13 Database: Compendex Compilation and indexing terms, © 2016 Elsevier Inc. |
2楼2016-05-20 09:44:24