Scalable biomedical Named Entity Recognition: investigation of a database-supported SVM approach
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[1] Claudio Giuliano,et al. Simple Information Extraction (SIE) , 2005 .
[2] Thorsten Joachims,et al. Making large scale SVM learning practical , 1998 .
[3] Shigeo Abe,et al. Support Vector Machines for Pattern Classification (Advances in Pattern Recognition) , 2005 .
[4] Nigel Collier,et al. Introduction to the Bio-entity Recognition Task at JNLPBA , 2004, NLPBA/BioNLP.
[5] Marcos M. Campos,et al. SVM in Oracle Database 10g: Removing the Barriers to Widespread Adoption of Support Vector Machines , 2005, VLDB.
[6] Mona Soliman Habib,et al. Addressing Scalability Issues of Named Entity Recognition Using Multi-Class Support Vector Machines , 2008 .
[7] Shigeo Abe. Support Vector Machines for Pattern Classification , 2010, Advances in Pattern Recognition.
[8] Hae-Chang Rim,et al. Biomedical named entity recognition using two-phase model based on SVMs , 2004, J. Biomed. Informatics.
[9] Gary Geunbae Lee,et al. POSBIOTM-NER in the Shared Task of BioNLP/NLPBA2004 , 2004, NLPBA/BioNLP.
[10] J. Kalita,et al. Language and Domain-Independent Named Entity Recognition : Experiment using SVM and High-Dimensional Features , 2007 .
[11] Alessandro Cimatti,et al. Istituto per La Ricerca Scientifica E Tecnologica , 1996 .
[13] Zhou GuoDong,et al. Recognizing names in biomedical texts using hidden Markov model and SVM plus sigmoid , 2004 .
[14] Hae-Chang Rim,et al. Incorporating Lexical Knowledge into Biomedical NE Recognition , 2004, NLPBA/BioNLP.
[15] Kristin P. Bennett,et al. Support vector machines: hype or hallelujah? , 2000, SKDD.
[16] Thorsten Joachims,et al. Text Categorization with Support Vector Machines: Learning with Many Relevant Features , 1998, ECML.
[17] Koby Crammer,et al. On the Algorithmic Implementation of Multiclass Kernel-based Vector Machines , 2002, J. Mach. Learn. Res..
[18] R. Tibshirani,et al. An introduction to the bootstrap , 1993 .
[19] Guodong Zhou,et al. Recognizing Names in Biomedical Texts using Hidden Markov Model and SVM plus Sigmoid , 2004, NLPBA/BioNLP.
[20] Jun'ichi Tsujii,et al. GENIA corpus - a semantically annotated corpus for bio-textmining , 2003, ISMB.
[21] Thorsten Joachims,et al. A support vector method for multivariate performance measures , 2005, ICML.
[22] Venu Govindaraju,et al. Half-Against-Half Multi-class Support Vector Machines , 2005, Multiple Classifier Systems.
[23] Thorsten Joachims,et al. Learning to classify text using support vector machines - methods, theory and algorithms , 2002, The Kluwer international series in engineering and computer science.
[24] Chih-Jen Lin,et al. A comparison of methods for multiclass support vector machines , 2002, IEEE Trans. Neural Networks.
[25] Su Jian,et al. Exploring Deep Knowledge Resources in Biomedical Name Recognition , 2004, NLPBA/BioNLP.
[26] Thomas Hofmann,et al. Large Margin Methods for Structured and Interdependent Output Variables , 2005, J. Mach. Learn. Res..
[27] Nello Cristianini,et al. Large Margin DAGs for Multiclass Classification , 1999, NIPS.
[28] Marc Rössler,et al. Adapting an NER-System for German to the Biomedical Domain , 2004, NLPBA/BioNLP.
[29] Thorsten Joachims,et al. Training linear SVMs in linear time , 2006, KDD '06.
[30] Ethem Alpaydin,et al. Introduction to machine learning , 2004, Adaptive computation and machine learning.
[31] Vladimir Vapnik,et al. Statistical learning theory , 1998 .
[32] Thomas Hofmann,et al. Support vector machine learning for interdependent and structured output spaces , 2004, ICML.
[33] Ulrich H.-G. Kreßel,et al. Pairwise classification and support vector machines , 1999 .
[34] Stefan Rüping. Support Vector Machines in Relational Databases , 2002, SVM.