{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,12,2]],"date-time":"2023-12-02T22:08:11Z","timestamp":1701554891869},"reference-count":31,"publisher":"Cambridge University Press (CUP)","issue":"1","license":[{"start":{"date-parts":[[2015,12,14]],"date-time":"2015-12-14T00:00:00Z","timestamp":1450051200000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Nat. Lang. Eng."],"published-print":{"date-parts":[[2017,1]]},"abstract":"<jats:title>Abstract<\/jats:title><jats:p>Finding translations for technical terms is an important problem in machine translation. In particular, in highly specialized domains such as biology or medicine, it is difficult to find bilingual experts to annotate sufficient cross-lingual texts in order to train machine translation systems. Moreover, new terms are constantly being generated in the biomedical community, which makes it difficult to keep the translation dictionaries up to date for all language pairs of interest. Given a biomedical term in one language (source language), we propose a method for detecting its translations in a different language (target language). Specifically, we train a binary classifier to determine whether two biomedical terms written in two languages are translations. Training such a classifier is often complicated due to the lack of common features between the source and target languages. We propose several feature space concatenation methods to successfully overcome this problem. Moreover, we study the effectiveness of contextual and character <jats:italic>n<\/jats:italic>-gram features for detecting term translations. Experiments conducted using a standard dataset for biomedical term translation show that the proposed method outperforms several competitive baseline methods in terms of mean average precision and top-<jats:italic>k<\/jats:italic> translation accuracy.<\/jats:p>","DOI":"10.1017\/s1351324915000431","type":"journal-article","created":{"date-parts":[[2015,12,14]],"date-time":"2015-12-14T08:04:12Z","timestamp":1450080252000},"page":"31-51","source":"Crossref","is-referenced-by-count":5,"title":["A classification approach for detecting cross-lingual biomedical term translations"],"prefix":"10.1017","volume":"23","author":[{"given":"H.","family":"HAKAMI","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"D.","family":"BOLLEGALA","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"56","published-online":{"date-parts":[[2015,12,14]]},"reference":[{"key":"S1351324915000431_ref010","doi-asserted-by":"publisher","DOI":"10.1017\/S135132491000015X"},{"key":"S1351324915000431_ref024","doi-asserted-by":"publisher","DOI":"10.1007\/s10772-009-9043-7"},{"key":"S1351324915000431_ref015","first-page":"111","volume-title":"Proceedings of the European Chapter for the Association for Computational Linguistics (ACL)","author":"Kontonatsios","year":"2014"},{"key":"S1351324915000431_ref003","first-page":"340","volume-title":"Proceedings of HTL-NAACL\u201907","author":"Bollegala","year":"2007"},{"key":"S1351324915000431_ref019","unstructured":"Mikolov T. , Tau Yih W. , and Zweig G. 2013b. Linguistic regularities in continous space word representations. In NAACL\u201913, pp. 746\u201351."},{"key":"S1351324915000431_ref017","doi-asserted-by":"publisher","DOI":"10.1023\/B:INRT.0000009441.78971.be"},{"key":"S1351324915000431_ref026","first-page":"141","volume-title":"Proceedings of the 13th Conference of the European Chapter of the Association for Computational Linguistics","author":"Tiedemann","year":"2012"},{"key":"S1351324915000431_ref023","doi-asserted-by":"publisher","DOI":"10.3115\/1034678.1034756"},{"key":"S1351324915000431_ref013","doi-asserted-by":"publisher","DOI":"10.1197\/jamia.M2314"},{"key":"S1351324915000431_ref030","first-page":"107","article-title":"Using distributional similarity to organise biomedical terminology","volume":"2","author":"Weeds","year":"2007","journal-title":"Application-Driven Terminology Engineering"},{"key":"S1351324915000431_ref029","doi-asserted-by":"publisher","DOI":"10.3115\/1626355.1626360"},{"key":"S1351324915000431_ref001","doi-asserted-by":"publisher","DOI":"10.1162\/coli_a_00016"},{"key":"S1351324915000431_ref016","unstructured":"Lin D. 1998. Automatic retrieval and clustering of similar words. In ACL 1998, pp. 768\u201374."},{"key":"S1351324915000431_ref011","doi-asserted-by":"publisher","DOI":"10.1186\/1471-2105-7-3"},{"key":"S1351324915000431_ref014","first-page":"1701","volume-title":"Proceedings of Empirical Methods in Natural Language Processing (EMNLP)","author":"Kontonatsios","year":"2014"},{"key":"S1351324915000431_ref004","unstructured":"Bostr\u00f6m H. 2007. Estimating class probabilities in random forests. In International Conference on Machine Learning and Applications, pp. 211\u20136."},{"key":"S1351324915000431_ref008","first-page":"684","volume-title":"Proceedings of LREC","author":"Claveau","year":"2008"},{"key":"S1351324915000431_ref018","unstructured":"Mikolov T. , Chen K. , and Dean J. 2013a. Efficient estimation of word representation in vector space. CoRR abs\/1301.3781."},{"key":"S1351324915000431_ref025","first-page":"27","volume-title":"Proceedings of Building and using Comparable Corpora Workshop","author":"Saralegi","year":"2008"},{"key":"S1351324915000431_ref022","first-page":"793","article-title":"Predicting lexical relations between biomedical terms: towards a multilingual morphosemantics-based system","volume":"116","author":"Namer","year":"2005","journal-title":"Studies in Health Technology and Informatics"},{"key":"S1351324915000431_ref020","unstructured":"Mitchell J. , and Lapata M. 2008. Vector-based models of semantic composition. In ACL-HLT\u201908, pp. 236\u201344."},{"key":"S1351324915000431_ref007","first-page":"1","volume-title":"Proceedings of the 19th International Conference on Computational Linguistics","author":"Chiao","year":"2002"},{"key":"S1351324915000431_ref006","unstructured":"Chan Y. S. , and Ng H. T. 2005. Word sense disambiguation with distribution estimation. In IJCAI\u201905, pp. 1010\u20135."},{"key":"S1351324915000431_ref031","first-page":"285","volume-title":"Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics","author":"Xi","year":"2012"},{"key":"S1351324915000431_ref012","doi-asserted-by":"publisher","DOI":"10.1145\/1596990.1596995"},{"key":"S1351324915000431_ref009","doi-asserted-by":"publisher","DOI":"10.1093\/biomet\/26.4.404"},{"key":"S1351324915000431_ref021","first-page":"301","volume-title":"Proceedings of Annual Meeting of the Association for Computational Linguistics (short-papers)","author":"Nakov","year":"2012"},{"key":"S1351324915000431_ref027","first-page":"676","volume-title":"Proceedings of Recent Advances in Natural Language Processing","author":"Tiedemann","year":"2013"},{"key":"S1351324915000431_ref028","doi-asserted-by":"crossref","first-page":"141","DOI":"10.1613\/jair.2934","article-title":"From frequency to meaning: vector space models of semantics","volume":"37","author":"Turney","year":"2010","journal-title":"Journal of Aritificial Intelligence Research"},{"key":"S1351324915000431_ref005","doi-asserted-by":"publisher","DOI":"10.1023\/A:1010933404324"},{"key":"S1351324915000431_ref002","first-page":"1222","volume-title":"Proceedings of IJCAI","author":"Bollegala","year":"2015"}],"container-title":["Natural Language Engineering"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S1351324915000431","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,4,18]],"date-time":"2019-04-18T05:01:58Z","timestamp":1555563718000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S1351324915000431\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2015,12,14]]},"references-count":31,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2017,1]]}},"alternative-id":["S1351324915000431"],"URL":"https:\/\/doi.org\/10.1017\/s1351324915000431","relation":{},"ISSN":["1351-3249","1469-8110"],"issn-type":[{"value":"1351-3249","type":"print"},{"value":"1469-8110","type":"electronic"}],"subject":[],"published":{"date-parts":[[2015,12,14]]}}}