Ananiadou S, McNaught J (2005) Text mining for biology and biomedicine. Artech House, Norwood
Google Scholar
Chen L, Liu H, Friedman C (2005) Gene name ambiguity of eukaryotic nomenclatures. Bioinformatics 21(2):248–256
Article
Google Scholar
Kozareva Z, Ferrandez O, Montoyo A, Munoz R, Suarez A (2007) Combining data-driven systems for improving named entity recognition. Data Knowl Eng 61(3):449–466
Article
Google Scholar
Biolchini J, Mian PG, Natali ACC, Travassos GH (2005) Systematic review in software engineering. System Engineering and Computer Science Department COPPE/UFRJ, Technical report ES, 679(05)
Kitchenham B (2004) Procedures for performing systematic reviews. Technical report, Keele University and NICTA
Kim J-D, Ohta T, Tsuruoka Y, Tateisi Y, Collier N (2004) Introduction to the bio-entity recognition task at JNLPBA. In: JNLPBA’04: Proceedings of the international joint workshop on natural language processing in biomedicine and its applications, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 70–75
Chapter
Google Scholar
Tsai RT-H, Wu S-H, Chou W-C, Lin Y-C, He D, Hsiang J, Sungand T-Y, Hsu W-L (2006) Various criteria in the evaluation of biomedical named entity recognition. BMC Bioinform 7:92
Article
Google Scholar
Sasaki Y, Tsuruoka Y, McNaught J, Ananiadou S (2008) How to make the most of NE dictionaries in statistical NER. BMC Bioinform 9(Suppl 11):S5
Article
Google Scholar
Sun B, Mitra P, Giles CL (2008) Mining, indexing, and searching for textual chemical molecule information on the web. In: WWW ’08: Proceedings of the 17th international conference on World Wide Web. ACM, New York, pp 735–744
Chapter
Google Scholar
Hakenberg J, Plake C, Leaman R, Schroeder M, Gonzalez G (2008) Inter-species normalization of gene mentions with GNAT. Bioinformatics 24(16):126–132
Article
Google Scholar
Tan H, Lambrix P (2009) Selecting an ontology for biomedical text mining. In: BioNLP ’09: Proceedings of the workshop on BioNLP, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 55–62
Chapter
Google Scholar
Vlachos A (2007) Evaluating and combining biomedical named entity recognition systems. In: BioNLP ’07: Proceedings of the workshop on BioNLP 2007, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 199–206
Chapter
Google Scholar
Jijkoun V, Khalid MA, Marx M, de Rijke M (2008) Named entity normalization in user generated content. In: AND ’08: proceedings of the second workshop on analytics for noisy unstructured text data. ACM, New York, pp 23–30
Chapter
Google Scholar
Sarafraz F, Eales J, Mohammadi R, Dickerson J, Robertson D, Nenadic G (2009) Biomedical event detection using rules, conditional random fields and parse tree distances. In: BioNLP ’09: proceedings of the workshop on BioNLP, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 115–118
Chapter
Google Scholar
Shi Z, Sarkar A, Popowich F (2007) Simultaneous identification of biomedical named-entity and functional relations using statistical parsing techniques. In: NAACL ’07: human language technologies 2007: the conference of the North American; Companion volume, Short papers on XX, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 161–164
Google Scholar
Liu H, Blouin C, Keselj V (2009) Identifying interaction sentences from biological literature using automatically extracted patterns. In: BioNLP ’09: proceedings of the workshop on BioNLP, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 133–141
Chapter
Google Scholar
Cohen KB, Verspoor K, Johnson HL, Roeder C, Ogren PV, Baumgartner WA Jr, White E, Tipney H, Hunter L (2009) High-precision biological event extraction with a concept recognizer. In: BioNLP ’09: proceedings of the workshop on BioNLP, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 50–58
Chapter
Google Scholar
Aleman-Meza B, Nagarajan M, Ding L, Sheth A, Arpinar IB, Joshi A, Finin T (2008) Scalable semantic analytics on social networks for addressing the problem of conflict of interest detection. ACM Trans Web 2(1):1–29
Article
Google Scholar
Alpaydin E (2004) Introduction to machine learning. MIT Press, Cambridge
Google Scholar
Jurafsky D, Martin JH (2009) Speech and language processing, 2nd edn. Prentice-Hall, New York
Google Scholar
Joachims T (1999) Advances in kernel methods: support vector learning. In: Making large-scale support vector machine learning practical. MIT Press, Cambridge, pp 169–184
Google Scholar
Vlachos A (2007) Evaluating and combining biomedical named entity recognition systems. In: BioNLP ’07: proceedings of the workshop on BioNLP 2007, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 199–206
Chapter
Google Scholar
Lafferty J, McCallum A, Pereira F (2001) Conditional random fields: Probabilistic models for segmenting and labeling sequence data. In: Proceedings of the eighteenth international conference on machine learning, pp 282–289
Google Scholar
Groves RM, Fowler FJ Jr, Couper MP, Lepkowski JM, Singer E, Tourangeau R (2009) Survey methodology, 2nd edn. Wiley-Blackwell, New York
Google Scholar
Overview articles. http://www.signalprocessingsociety.org/publications/overview-articles/
Chan S-K, Lam W, Yu X (2007) A cascaded approach to biomedical named entity recognition using a unified model. In: Data mining. ICDM 2007. Seventh IEEE international conference on, Oct 2007, pp 93–102
Google Scholar
Wang H, Zhao T, Liu J (2008) Multi-agent classifiers fusion strategy for biomedical named entity recognition. In: BioMedical engineering and informatics. BMEI 2008. International conference on, May 2008, vol 1, pp 311–315
Chapter
Google Scholar
Kim J-D, Ohta T, Teteisi Y, Tsujii J (2003) GENIA corpus—a semantically annotated corpus for bio-textmining. Bioinformatics 19(Suppl 1):180–182
Article
Google Scholar
Corbett P, Batchelor C, Teufel S (2007) Annotation of chemical named entities BioNLP 2007: biological, translational, and clinical language processing, Prague, Czech Republic, pp 57–64
Corbett P, Copestake A (2008) Cascaded classifiers for confidence-based chemical named entity recognition. BMC Bioinformatics 9(Suppl 11):S4
Article
Google Scholar
Sasaki Y, Tsuruoka Y, McNaught J, Ananiadou S (2008) How to make the most of ne dictionaries in statistical ner. In: BioNLP ’08: proceedings of the workshop on current trends in biomedical natural language processing, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 63–70
Chapter
Google Scholar
Neves ML, Carazo JM, Pascual-Montano A (2009) Extraction of biomedical events using case-based reasoning. In: BioNLP ’09: proceedings of the workshop on BioNLP, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 68–76
Chapter
Google Scholar
Li Y, Lin H, Yang Z (2007) Two approaches for biomedical text classification. In: Bioinformatics and biomedical engineering. ICBBE 2007. The 1st international conference on, July 2007, pp 310–313
Chapter
Google Scholar
Viola P, Jones M (2001) Fast multi-view face detection. In: Proc of CVPR
Google Scholar
Yoshida K, Tsujii J (2007) Reranking for biomedical named-entity recognition. In: BioNLP ’07: proceedings of the workshop on BioNLP 2007, Morristown, NJ, USA. Association for Computational Linguistics, Menlo Park, pp 209–216
Chapter
Google Scholar
Gu B, Dahl V, Popowich F (2007) Recognizing biomedical named entities in the absence of human annotated corpora. In: Natural language processing and knowledge engineering. NLP-KE 2007. International conference on, August 30 2007–Sept 1, pp 74–81
Chapter
Google Scholar
Cohen KB, Fox L, Ogren PV, Hunter L (2005) Empirical data on corpus design and usage in biomedical natural language processing. In: AMIA symposium, pp 156–160
Google Scholar
Jurafsky D, Martin JH (2000) Speech and language processing: an introduction to natural language processing, computational linguistics, and speech recognition. Prentice Hall PTR, New York
Google Scholar