{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,11]],"date-time":"2024-09-11T05:31:34Z","timestamp":1726032694533},"publisher-location":"Cham","reference-count":51,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783030181284"},{"type":"electronic","value":"9783030181291"}],"license":[{"start":{"date-parts":[[2019,1,1]],"date-time":"2019-01-01T00:00:00Z","timestamp":1546300800000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2019]]},"DOI":"10.1007\/978-3-030-18129-1_4","type":"book-chapter","created":{"date-parts":[[2019,6,20]],"date-time":"2019-06-20T07:24:18Z","timestamp":1561015458000},"page":"61-86","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Detecting Sections and Entities in Court Decisions Using HMM and CRF Graphical Models"],"prefix":"10.1007","author":[{"given":"Gildas Tagny","family":"Ngomp\u00e9","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"S\u00e9bastien","family":"Harispe","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Guillaume","family":"Zambrano","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Jacky","family":"Montmain","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"St\u00e9phane","family":"Mussard","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2019,6,21]]},"reference":[{"key":"4_CR1","unstructured":"Balikas, G., Partalas, I., & Amin, M. -R. (July 2017). On the effectiveness of feature set augmentation using clusters of word embeddings. In Proceedings of ACM Conference, Washington, DC, USA, (p. 5)."},{"key":"4_CR2","unstructured":"Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. The Journal of Machine Learning Research, 3, 993\u20131022."},{"issue":"4","key":"4_CR3","doi-asserted-by":"publisher","first-page":"1007","DOI":"10.1007\/s10579-013-9215-6","volume":"47","author":"K Bontcheva","year":"2013","unstructured":"Bontcheva, K., Cunningham, H., Roberts, I., Roberts, A., Tablan, V., Aswani, N., et al. (2013). Gate teamware: A web-based, collaborative text annotation framework. Language Resources and Evaluation, 47(4), 1007\u20131029.","journal-title":"Language Resources and Evaluation"},{"key":"4_CR4","doi-asserted-by":"crossref","unstructured":"Cardellino, C., & Teruel, M., et al. (2017). A low-cost, high-coverage legal named entity recognizer, classifier and linker. In Proceedings of the 16th edition of the International Conference on Articial Intelligence and Law (pp. 9\u201318). ACM.","DOI":"10.1145\/3086512.3086514"},{"key":"4_CR5","unstructured":"Chang, Y. -S., & Sung, Y. -H. (2005). Applying name entity recognition to informal text. Stanford CS224N\/Ling237 Final Project Report."},{"key":"4_CR6","unstructured":"Chau, M., Xu, J.\u00a0J., & Chen, H. (2002). Extracting meaningful entities from police narrative reports. In Proceedings of the 2002 Annual National conference on Digital Government Research. Digital Government Society of North America."},{"key":"4_CR7","unstructured":"Chiticariu, L., Krishnamurthy, R., Li, Y., Reiss, F., & Vaithyanathan, S. (2010). Domain adaptation of rule-based annotators for named-entity recognition tasks. In Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing (pp. 1002\u20131012). Association for Computational Linguistics."},{"key":"4_CR8","unstructured":"Cretin, L. (2014). L\u2019opinion des fran\u00e7ais sur la justice. INFOSTAT JUSTICE, 125."},{"key":"4_CR9","doi-asserted-by":"crossref","unstructured":"Dozier, C., Kondadadi, R., Light, M., Vachher, A., Veeramachaneni, S., & Wudali, R. (2010). Named entity recognition and resolution in legal text. In Semantic Processing of Legal Texts (pp. 27\u201343). Springer.","DOI":"10.1007\/978-3-642-12837-0_2"},{"key":"4_CR10","doi-asserted-by":"crossref","unstructured":"Finkel, J.\u00a0R., Grenager, T., & Manning, C. (2005). Incorporating non-local information into information extraction systems by Gibbs sampling. In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics (pp. 363\u2013370). Association for Computational Linguistics.","DOI":"10.3115\/1219840.1219885"},{"key":"4_CR11","doi-asserted-by":"crossref","unstructured":"Galliano, S., Gravier, G., & Chaubard, L. (2009). The ester 2 evaluation campaign for the rich transcription of French radio broadcasts. In Tenth Annual Conference of the International Speech Communication Association.","DOI":"10.21437\/Interspeech.2009-680"},{"key":"4_CR12","unstructured":"Guo, H., & Zhu, H., et al. (2009). Domain adaptation with latent semantic association for named entity recognition. In Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics (pp. 281\u2013289)."},{"key":"4_CR13","doi-asserted-by":"crossref","unstructured":"Hanisch, D., & Fundel, K., et\u00a0al. (2005). Prominer: Rule-based protein and gene entity recognition. BMC Bioinformatics, 6(1), S14.","DOI":"10.1186\/1471-2105-6-S1-S14"},{"key":"4_CR14","unstructured":"Huang, Z., Xu, W., & Yu, K. (2015). Bidirectional LSTM-CRF models for sequence tagging. arXiv:1508.01991 ."},{"key":"4_CR15","doi-asserted-by":"crossref","unstructured":"Konkol, M., & Konop\u00edk, M. (2015). Segment representations in named entity recognition. In International Conference on Text, Speech, and Dialogue (pp. 61\u201370). Springer.","DOI":"10.1007\/978-3-319-24033-6_7"},{"key":"4_CR16","first-page":"51","volume-title":"Lecture Notes in Computer Science","author":"Vincent Kr\u00ed\u017e","year":"2014","unstructured":"Kr\u00ed\u017e, V., Hladk\u00e1, B., et\u00a0al. (2014). Statistical Recognition of References in Czech Court Decisions (pp. 51\u201361). Cham: Springer International Publishing."},{"key":"4_CR17","unstructured":"Lafferty, J., McCallum, A., & Pereira, F.\u00a0C. (2001). Conditional random fields: Probabilistic models for segmenting and labeling sequence data. International Conference on Machine Learning."},{"key":"4_CR18","doi-asserted-by":"crossref","unstructured":"Lam, H.-P., Hashmi, M., & Scofield, B. (2016). Enabling reasoning with legalruleml. In International Symposium on Rules and Rule Markup Languages for the Semantic Web (pp. 241\u2013257). Springer.","DOI":"10.1007\/978-3-319-42019-6_16"},{"key":"4_CR19","unstructured":"Lample, G., & Ballesteros, M., et\u00a0al. (2016). Neural architectures for named entity recognition. arXiv:1603.01360 ."},{"key":"4_CR20","first-page":"379","volume":"2","author":"Y Li","year":"2002","unstructured":"Li, Y., Zaragoza, H., Herbrich, R., Shawe-Taylor, J., & Kandola, J. (2002). The perceptron algorithm with uneven margins. ICML, 2, 379\u2013386.","journal-title":"ICML"},{"key":"4_CR21","doi-asserted-by":"crossref","unstructured":"Liu, D. C., & Nocedal, J. (1989). On the limited memory BFGS method for large scale optimization. Mathematical Programming, 45(1), 503\u2013528.","DOI":"10.1007\/BF01589116"},{"key":"4_CR22","unstructured":"Liu, H., & Motoda, H. (2012). Feature selection for knowledge discovery and data mining, volume 454. Springer Science & Business Media."},{"key":"4_CR23","unstructured":"Ma, X., & Hovy, E. (2016). End-to-end sequence labeling via bi-directional LSTM-CNNs-CRF. arXiv:1603.01354 ."},{"issue":"5","key":"4_CR24","doi-asserted-by":"publisher","first-page":"482","DOI":"10.1016\/j.csi.2012.09.004","volume":"35","author":"M Marrero","year":"2013","unstructured":"Marrero, M., Urbano, J., et al. (2013). Named entity recognition: Fallacies, challenges and opportunities. Computer Standards & Interfaces, 35(5), 482\u2013489.","journal-title":"Computer Standards & Interfaces"},{"key":"4_CR25","unstructured":"McCallum, A.\u00a0K. (2002). MALLET: A Machine Learning for Language Toolkit. http:\/\/mallet.cs.umass.edu\/ ."},{"issue":"2","key":"4_CR26","doi-asserted-by":"publisher","first-page":"127","DOI":"10.1023\/A:1009953814988","volume":"3","author":"AK McCallum","year":"2000","unstructured":"McCallum, A. K., Nigam, K., et al. (2000). Automating the construction of internet portals with machine learning. Information Retrieval, 3(2), 127\u2013163.","journal-title":"Information Retrieval"},{"key":"4_CR27","doi-asserted-by":"crossref","unstructured":"Mikheev, A., Moens, M., & Grover, C. (1999). Named entity recognition without gazetteers. In Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics (pp. 1\u20138). Association for Computational Linguistics.","DOI":"10.3115\/977035.977037"},{"key":"4_CR28","unstructured":"Nallapati, R., Surdeanu, M., & Manning, C. (2010). Blind domain transfer for named entity recognition using generative latent topic models. In Proceedings of the NIPS 2010 Workshop on Transfer Learning Via Rich Generative Models (pp. 281\u2013289)."},{"key":"4_CR29","doi-asserted-by":"crossref","unstructured":"Palmer, D.\u00a0D., & Day, D.\u00a0S. (1997). A statistical profile of the named entity task. In Proceedings of the Fifth Conference on Applied Natural Language Processing (pp. 190\u2013193). Association for Computational Linguistics.","DOI":"10.3115\/974557.974585"},{"key":"4_CR30","unstructured":"Persson, C. (2012). Machine Learning for Tagging of Biomedical Literature. Closing project report, Technical University of Denmark, DTU Informatics."},{"key":"4_CR31","unstructured":"Petrillo, M., & Baycroft, J. (2010). Introduction to manual annotation. Fairview Research."},{"key":"4_CR32","unstructured":"Plamondon, L., Lapalme, G., & Pelletier, F. (2004). Anonymisation de d\u00e9cisions de justice. In XIe Conf\u00e9rence sur le Traitement Automatique des Langues Naturelles (TALN 2004) (pp. 367\u2013376)."},{"key":"4_CR33","doi-asserted-by":"crossref","unstructured":"Polifroni, J., & Mairesse, F. (2011). Using latent topic features for named entity extraction in search queries. INTERSPEECH, 2129\u20132132.","DOI":"10.21437\/Interspeech.2011-558"},{"issue":"11","key":"4_CR34","doi-asserted-by":"publisher","first-page":"1119","DOI":"10.1016\/0167-8655(94)90127-9","volume":"15","author":"P Pudil","year":"1994","unstructured":"Pudil, P., Novovi\u010dov\u00e1, J., & Kittler, J. (1994). Floating search methods in feature selection. Pattern Recognition Letters, 15(11), 1119\u20131125.","journal-title":"Pattern Recognition Letters"},{"issue":"2","key":"4_CR35","doi-asserted-by":"publisher","first-page":"257","DOI":"10.1109\/5.18626","volume":"77","author":"LR Rabiner","year":"1989","unstructured":"Rabiner, L. R. (1989). A tutorial on hidden Markov models and selected applications in speech recognition. Proceedings of the IEEE, 77(2), 257\u2013286.","journal-title":"Proceedings of the IEEE"},{"key":"4_CR36","unstructured":"Raman, B., & Ioerger, T. R. (2003). Enhancing learning using feature and example selection. College Station, TX, USA: Texas A&M University."},{"key":"4_CR37","unstructured":"Rosset, S., Grouin, C., & Zweigenbaum, P. (2011). Entit\u00e9s nomm\u00e9es structur\u00e9es: guide d\u2019annotation Quaero. LIMSI-Centre national de la recherche scientifique."},{"key":"4_CR38","unstructured":"Schmid, H. (2013). Probabilistic part-of-speech tagging using decision trees. In New methods in language processing (pp. 154). Routledge."},{"key":"4_CR39","unstructured":"Siniakov, P. (2008). GROPUS an Adaptive Rule-based Algorithm for Information Extraction. PhD thesis, Freie Universit\u00e4t Berlin."},{"key":"4_CR40","unstructured":"Surdeanu, M., Nallapati, R., & Manning, C. (2010). Legal claim identification: Information extraction with hierarchically labeled data. In Proceedings of the LREC 2010 Workshop on the Semantic Processing of Legal Texts."},{"key":"4_CR41","unstructured":"Tellier, I., Dupont, Y., & Courmet, A. (2012). Un segmenteur-\u00e9tiqueteur et un chunker pour le Fran\u00e7ais. JEP-TALN-RECITAL 2012, page\u00a07."},{"key":"4_CR42","unstructured":"Tjong Kim\u00a0Sang, E.\u00a0F., & De\u00a0Meulder, F. (2003). Introduction to the CONLL-2003 shared task: Language-independent named entity recognition. In Proceedings of the Seventh Conference on Natural Language Learning at HLT-NAACL 2003 - Volume 4, CONLL \u201903, pp. 142\u2013147, Stroudsburg, PA, USA. Association for Computational Linguistics."},{"issue":"5","key":"4_CR43","first-page":"360","volume":"37","author":"AJ Viera","year":"2005","unstructured":"Viera, A. J., Garrett, J. M., et al. (2005). Understanding interobserver agreement: The kappa statistic. Fam Med, 37(5), 360\u2013363.","journal-title":"Fam Med"},{"issue":"2","key":"4_CR44","doi-asserted-by":"publisher","first-page":"260","DOI":"10.1109\/TIT.1967.1054010","volume":"13","author":"AJ Viterbi","year":"1967","unstructured":"Viterbi, A. J. (1967). Error bounds for convolutional codes and an asymptotically optimum decoding algorithm. IEEE Transactions on Information Theory, 13(2), 260\u2013269.","journal-title":"IEEE Transactions on Information Theory"},{"key":"4_CR45","unstructured":"Wallach, H.\u00a0M. (2004). Conditional random fields: An introduction. University of Pennsylvania Department of Computer and Information Science Technical Report No. MS-CIS-04-21."},{"issue":"4","key":"4_CR46","first-page":"10","volume":"53","author":"LR Welch","year":"2003","unstructured":"Welch, L. R. (2003). Hidden Markov models and the Baum-Welch algorithm. IEEE Information Theory Society Newsletter, 53(4), 10\u201313.","journal-title":"IEEE Information Theory Society Newsletter"},{"key":"4_CR47","unstructured":"Witten, I.\u00a0H., & Bray, Z., et\u00a0al. (1999). Using language models for generic entity extraction. In Proceedings of the ICML Workshop on Text Mining."},{"key":"4_CR48","doi-asserted-by":"crossref","unstructured":"Wu, Y., Zhao, J., & Xu, B. (2003). Chinese named entity recognition combining a statistical model with human knowledge. In Proceedings of the ACL 2003 workshop on Multilingual and mixed-language named entity recognition-Volume 15 (pp. 65\u201372). Association for Computational Linguistics.","DOI":"10.3115\/1119384.1119393"},{"key":"4_CR49","unstructured":"Wyner, A., & Peters, W. (2012). Semantic annotations for legal text processing using GATE Teamware. In Semantic Processing of Legal Texts (SPLeT-2012) Workshop Programme p. 34."},{"key":"4_CR50","unstructured":"Xiao, R. (2010). Handbook of natural language processing, chapter 7 - Corpus Creation, pp. 146\u2013165. Chapman and Hall, second edition."},{"key":"4_CR51","unstructured":"Zhu, X. (2010). Conditional random fields. CS769 Spring 2010 Advanced Natural Language Processing. http:\/\/pages.cs.wisc.edu\/~jerryzhu\/cs769\/CRF.pdf ."}],"container-title":["Studies in Computational Intelligence","Advances in Knowledge Discovery and Management"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-030-18129-1_4","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,9,21]],"date-time":"2022-09-21T07:22:51Z","timestamp":1663744971000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-030-18129-1_4"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019]]},"ISBN":["9783030181284","9783030181291"],"references-count":51,"URL":"https:\/\/doi.org\/10.1007\/978-3-030-18129-1_4","relation":{},"ISSN":["1860-949X","1860-9503"],"issn-type":[{"type":"print","value":"1860-949X"},{"type":"electronic","value":"1860-9503"}],"subject":[],"published":{"date-parts":[[2019]]},"assertion":[{"value":"21 June 2019","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}}]}}