{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,6,19]],"date-time":"2025-06-19T04:39:51Z","timestamp":1750307991917,"version":"3.41.0"},"reference-count":12,"publisher":"Association for Computing Machinery (ACM)","issue":"1","license":[{"start":{"date-parts":[[2006,3,1]],"date-time":"2006-03-01T00:00:00Z","timestamp":1141171200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["ACM Transactions on Asian Language Information Processing"],"published-print":{"date-parts":[[2006,3]]},"abstract":"<jats:p>\n            In this paper, we present a two-phase biomedical NE-recognition method based on a ME model: we first recognize biomedical terms and then assign appropriate semantic classes to the recognized terms. In the two-phase NE-recognition method, the performance of the term-recognition phase is very important, because the semantic classification is performed on the region identified at the recognition phase. In this study, in order to improve the performance of term recognition, we try to incorporate lexical knowledge into pre- and postprocessing of the term-recognition phase. In the preprocessing step, we use domain-salient words as lexical knowledge obtained by corpus comparison. In the postprocessing step, we utilize \u03c7\n            <jats:sup>2<\/jats:sup>\n            -based collocations gained from Medline corpus. In addition, we use morphological patterns extracted from the training data as features for learning the ME-based classifiers. Experimental results show that the performance of NE-recognition can be improved by utilizing such lexical knowledge.\n          <\/jats:p>","DOI":"10.1145\/1131348.1131350","type":"journal-article","created":{"date-parts":[[2006,7,25]],"date-time":"2006-07-25T14:14:26Z","timestamp":1153836866000},"page":"4-21","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":10,"title":["ME-based biomedical named entity recognition using lexical knowledge"],"prefix":"10.1145","volume":"5","author":[{"given":"Kyung-Mi","family":"Park","sequence":"first","affiliation":[{"name":"Korea University, Seoul, Korea"}]},{"given":"Seon-Ho","family":"Kim","sequence":"additional","affiliation":[{"name":"Korea University, Seoul, Korea"}]},{"given":"Hae-Chang","family":"Rim","sequence":"additional","affiliation":[{"name":"Korea University, Seoul, Korea"}]},{"given":"Young-Sook","family":"Hwang","sequence":"additional","affiliation":[{"name":"Advanced Telecommunications Research Institute (ATR), Kyoto, Japan"}]}],"member":"320","published-online":{"date-parts":[[2006,3]]},"reference":[{"key":"e_1_2_1_1_1","first-page":"39","article-title":"A maximum-entropy approach to natural language processing","volume":"22","author":"Berger A.","year":"1996","unstructured":"Berger , A. , Pietra , S. , and Pietra , V. 1996 . A maximum-entropy approach to natural language processing . Computational Linguistics 22 , 1, 39 -- 71 . Berger, A., Pietra, S., and Pietra, V. 1996. A maximum-entropy approach to natural language processing. Computational Linguistics 22, 1, 39--71.","journal-title":"Computational Linguistics"},{"key":"e_1_2_1_2_1","volume-title":"Proceedings of the 6th Applied Natural Language Processing. 10","author":"Brants T.","year":"2000","unstructured":"Brants , T. 2000 . TnT---a statistical part-of-speech tagger . In Proceedings of the 6th Applied Natural Language Processing. 10 .3115\/974147.974178 Brants, T. 2000. TnT---a statistical part-of-speech tagger. In Proceedings of the 6th Applied Natural Language Processing. 10.3115\/974147.974178"},{"key":"e_1_2_1_3_1","volume-title":"Technical Report CMUCS-99-108, Carnegie Mellon University.","author":"Chen S.","year":"1999","unstructured":"Chen , S. and Rosenfeld , R . 1999 . A Gaussian prior for smoothing maximum entropy models. Technical Report CMUCS-99-108, Carnegie Mellon University. Chen, S. and Rosenfeld, R. 1999. A Gaussian prior for smoothing maximum entropy models. Technical Report CMUCS-99-108, Carnegie Mellon University."},{"volume-title":"Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004)","author":"Finkel J.","key":"e_1_2_1_4_1","unstructured":"Finkel , J. , Dingare , S. , Nguyen , H. , Nissim , M. , Sinclair , G. , and Manning , C . 2004. Exploiting context for biomedical entity recognition: from syntax to the web . Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004) . 88--91. Finkel, J., Dingare, S., Nguyen, H., Nissim, M., Sinclair, G., and Manning, C. 2004. Exploiting context for biomedical entity recognition: from syntax to the web. Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004). 88--91."},{"volume-title":"Proceedings of the 1st International Joint Conference on Natural Language Processing (IJCNLP-2004)","author":"Kim J. D.","key":"e_1_2_1_5_1","unstructured":"Kim , J. D. and Tsujii , J . 2004. Word folding: taking the snapshot of words instead of the whole . In Proceedings of the 1st International Joint Conference on Natural Language Processing (IJCNLP-2004) . 10.1007\/978-3-540-30211-7_43 Kim, J. D. and Tsujii, J. 2004. Word folding: taking the snapshot of words instead of the whole. In Proceedings of the 1st International Joint Conference on Natural Language Processing (IJCNLP-2004). 10.1007\/978-3-540-30211-7_43"},{"volume-title":"Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004)","author":"Kim J. D.","key":"e_1_2_1_6_1","unstructured":"Kim , J. D. , Ohta , T. , Tsuruoka , Y. , Tateisi , Y. , and Collier , N . 2004. Introduction to the bio-entity recognition task at JNLPBA . In Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004) . 70--75. Kim, J. D., Ohta, T., Tsuruoka, Y., Tateisi, Y., and Collier, N. 2004. Introduction to the bio-entity recognition task at JNLPBA. In Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004). 70--75."},{"volume-title":"Proceedings of the Conference on Natural Language Learning (CoNLL) 2000 Shared Task. 10","author":"Kudoh T.","key":"e_1_2_1_7_1","unstructured":"Kudoh , T. and Matsumoto , Y . 2000. Use of support vector learning for chunk identification . In Proceedings of the Conference on Natural Language Learning (CoNLL) 2000 Shared Task. 10 .3115\/1117601.1117635 Kudoh, T. and Matsumoto, Y. 2000. Use of support vector learning for chunk identification. In Proceedings of the Conference on Natural Language Learning (CoNLL) 2000 Shared Task. 10.3115\/1117601.1117635"},{"key":"e_1_2_1_8_1","volume-title":"Proceedings of the ACL 2003 Workshop on Natural Language Processing in Biomedicine. 33--40","author":"Lee K. J.","year":"1895","unstructured":"Lee , K. J. , Hwang , Y. S. , and Rim , H. C . 2003. Two-phase biomedical NE-recognition based on SVMs . In Proceedings of the ACL 2003 Workshop on Natural Language Processing in Biomedicine. 33--40 . 10.3115\/11 1895 8.1118963 Lee, K. J., Hwang, Y. S., and Rim, H. C. 2003. Two-phase biomedical NE-recognition based on SVMs. In Proceedings of the ACL 2003 Workshop on Natural Language Processing in Biomedicine. 33--40. 10.3115\/1118958.1118963"},{"key":"e_1_2_1_9_1","volume-title":"Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004)","author":"Settles B.","year":"2004","unstructured":"Settles , B. 2004 . Biomedical named entity recognition using conditional random fields and novel feature sets . Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004) . 104--107. Settles, B. 2004. Biomedical named entity recognition using conditional random fields and novel feature sets. Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004). 104--107."},{"volume-title":"Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004)","author":"Song Y.","key":"e_1_2_1_10_1","unstructured":"Song , Y. , Kim , E. J. , Lee , G. B. , and Yi , B. K . 2004. Biomedical named entity recognition using conditional random fields and novel feature sets . Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004) . 104--107. Song, Y., Kim, E. J., Lee, G. B., and Yi, B. K. 2004. Biomedical named entity recognition using conditional random fields and novel feature sets. Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004). 104--107."},{"volume-title":"Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004)","author":"Zhou G.","key":"e_1_2_1_11_1","unstructured":"Zhou , G. and Su , J . 2004. Exploring deep knowledge resources in biomedical name recognition . Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004) . 96--99. Zhou, G. and Su, J. 2004. Exploring deep knowledge resources in biomedical name recognition. Proceedings of the Joint Workshop on Natural Language Processing in Biomedicine and its Applications (JNLPBA-2004). 96--99."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1093\/bioinformatics\/bth060"}],"container-title":["ACM Transactions on Asian Language Information Processing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1131348.1131350","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/1131348.1131350","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T15:06:16Z","timestamp":1750259176000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/1131348.1131350"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2006,3]]},"references-count":12,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2006,3]]}},"alternative-id":["10.1145\/1131348.1131350"],"URL":"https:\/\/doi.org\/10.1145\/1131348.1131350","relation":{},"ISSN":["1530-0226","1558-3430"],"issn-type":[{"type":"print","value":"1530-0226"},{"type":"electronic","value":"1558-3430"}],"subject":[],"published":{"date-parts":[[2006,3]]},"assertion":[{"value":"2006-03-01","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}