目录

第六章：序列标注方法

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下载：序列标注方法【PDF，PPT】

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推荐读物

  1. Lawrence R. Rabiner, 1989. A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition. Proceedings of the IEEE, Vol. 77, No. 2, pp. 257-286.
  2. Klaus Krippendorff, 1995. On the Reliability of Unitizing Contiguous Data. Sociological Methodology, Vol. 25, pp. 47-76.
  3. R. Durbin, S. Eddy, A. Krogh and G. Mitchison, 1998. Biological Sequence Analysis: Probabilistic Models of Proteins and Nucleic Acids. Cambridge University Press, Cambridge.
  4. Sharon Goldwater and Thomas L. Griffiths, 2007. A Fully Bayesian Approach to Unsupervised Part-of-Speech Tagging. Proceedings of the 45th Annual Meeting of the Association of Computational Linguistics.
  5. John D. Lafferty, Andrew McCallum, and Fernando C. N. Pereira, 2001. Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data. Proceedings of the 18th International Conference on Machine Learning, pp. 282-289.
  6. Charles Sutton and Andrew McCallum, 2010. An Introduciton to Conditional Random Fields. eprint arXiv:1011.4088.
  7. Shuo Xu, Xin An, Lijun Zhu, Yunliang Zhang, and Haodong Zhang, 2015. A CRF-based System for Recognizing Chemical Entity Mentions (CEMs) in Biomedical Literature. Journal of Cheminformatics, Vol. 7, No. Suppl 1, pp. S11.
  8. Martin Krallinger, Obdulia Rabal, Florian Leitner, Miguel Vazquez, David Salgado, Zhiyong Lu, Robert Leaman, Yanan Lu, Donghong Ji, Daniel M Lowe, Roger A Sayle, Riza Theresa Batista-Navarro, Rafal Rak, Torsten Huber, Tim Rocktäschel, Sergio Matos, David Campos, Buzhou Tang, Hua Xu, Tsendsuren Munkhdalai, Keun Ho Ryu, S. V Ramanan, Senthil Nathan, Slavko Zitnik, Marko Bajec, Lutz Weber, Matthias Irmer, Saber A Akhondi, Jan A Kors, Shuo Xu, Xin An, Utpal Kumar Sikdar, Asif Ekbal, Masaharu Yoshioka, Thaer M Dieb, Miji Choi, Karin Verspoor, Madian Khabsa, C. Lee Giles, Hongfang Liu, Komandur Elayavilli Ravikumar, Andre Lamurias, Francisco M Couto, Hong-Jie Dai, Richard Tzong-Han Tsai, Caglar Ata, Tolga Can, Anabel Usie, Joaquim Cruz, Isabel Segura-Bedmar, Paloma Martinez, Julen Oyarzabal, and Alfonso Valencia, 2015. The CHEMDNER Corpus of Chemicals and Drugs and its Annotation Principles. Journal of Cheminformatics, Vol. 7, No. Suppl 1, pp. S2.
  9. Shengyu Liu, Buzhou Tang, Qingcai Chen, Xiaolong Wang, and Xiaoming Fan, 2015. Feature Engineering for Drug Name Recognition in Biomedical Texts: Feature Conjunction and Feature Selection. Computational and Mathematical Methods in Medicine, pp. 1-9.
  10. Liang Chen, Shuo Xu, Lijun Zhu, Jing Zhang, Xiaoping Lei, and Guancan Yang, 2020. A Deep Learning based Method for Extracting Semantic Information from Patent Documents. Scientometrics, Vol. 125, No. 1, pp. 289-312. Dataset
  11. Xin An, Jinghong Li, Shuo Xu, Liang Chen, and Wei Sun, 2021. An Improved Patent Similarity Measurement based on Entities and Semantic Relations. Journal of Informetrics, Vol. 15, No. 2, pp. 101135. Note
  12. Liang Chen, Shuo Xu, Lijun Zhu, Jing Zhang, Guancan Yang, and Haiyuan Xu, 2022. A Deep Learning based Method Benefiting from Characteristics of Patents for Semantic Relation Classification. Journal of Informetrics, Vol. 16, No. 3, pp. 101312.
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  14. Zheng Wang, Shuo Xu, Yibo Wang, Xiaojiao Chai, and Liang Chen, 2023. Bureau for Rapid Annotation Tool: Collaboration can do More among Variance Annotations. Aslib Journal of Information Management, Vol. 75, No. 3, pp. 523-534.
  15. Shuo Xu, Jiahao Li, Xin An, Shengnan Wang, Jianhua Liu, and Yuefu Zhang, 2025. Annotation and Identification of Scientific Data Sharing Information from Data Availability Section. Proceedings of the 20th International Conference on Scientometrics & Informetrics, pp. 119-127.