{"title":"Web-based technical term translation pairs mining for patent document translation","authors":"Feiliang Ren, Jingbo Zhu, Huizhen Wang","doi":"10.1109/NLPKE.2010.5587775","DOIUrl":null,"url":null,"abstract":"This paper proposes a simple but powerful approach for obtaining technical term translation pairs in patent domain from Web automatically. First, several technical terms are used as seed queries and submitted to search engineering. Secondly, an extraction algorithm is proposed to extract some key word translation pairs from the returned web pages. Finally, a multi-feature based evaluation method is proposed to pick up those translation pairs that are true technical term translation pairs in patent domain. With this method, we obtain about 8,890,000 key word translation pairs which can be used to translate the technical terms in patent documents. And experimental results show that the precision of these translation pairs are more than 99%, and the coverage of these translation pairs for the technical terms in patent documents are more than 84%.","PeriodicalId":259975,"journal":{"name":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-09-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 6th International Conference on Natural Language Processing and Knowledge Engineering(NLPKE-2010)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/NLPKE.2010.5587775","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
This paper proposes a simple but powerful approach for obtaining technical term translation pairs in patent domain from Web automatically. First, several technical terms are used as seed queries and submitted to search engineering. Secondly, an extraction algorithm is proposed to extract some key word translation pairs from the returned web pages. Finally, a multi-feature based evaluation method is proposed to pick up those translation pairs that are true technical term translation pairs in patent domain. With this method, we obtain about 8,890,000 key word translation pairs which can be used to translate the technical terms in patent documents. And experimental results show that the precision of these translation pairs are more than 99%, and the coverage of these translation pairs for the technical terms in patent documents are more than 84%.