An experiment in computational discrimination of English word senses
IBM Journal of Research and Development
A maximum entropy approach to natural language processing
Computational Linguistics
Foundations of statistical natural language processing
Foundations of statistical natural language processing
Document centered approach to text normalization
SIGIR '00 Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval
Speech and Language Processing: An Introduction to Natural Language Processing, Computational Linguistics, and Speech Recognition
Maximum entropy models for natural language ambiguity resolution
Maximum entropy models for natural language ambiguity resolution
Introduction to the special issue on word sense disambiguation: the state of the art
Computational Linguistics - Special issue on word sense disambiguation
Feature lattices for maximum entropy modelling
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 2
Unsupervised word sense disambiguation rivaling supervised methods
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Automatically identifying gene/protein terms in MEDLINE abstracts
Journal of Biomedical Informatics
Automatic acquisition of long-distance acronym definitions
Design and application of hybrid intelligent systems
Automatic sense disambiguation for acronyms
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Term identification in the biomedical literature
Journal of Biomedical Informatics - Special issue: Named entity recognition in biomedicine
A large scale, corpus-based approach for automatically disambiguating biomedical abbreviations
ACM Transactions on Information Systems (TOIS)
High throughput modularized NLP system for clinical text
ACLdemo '05 Proceedings of the ACL 2005 on Interactive poster and demonstration sessions
Journal of Biomedical Informatics
A term recognition approach to acronym recognition
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
AusDM '06 Proceedings of the fifth Australasian conference on Data mining and analystics - Volume 61
AMAP: automatically mining abbreviation expansions in programs to enhance software maintenance tools
Proceedings of the 2008 international working conference on Mining software repositories
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
Combined one sense disambiguation of abbreviations
HLT-Short '08 Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies: Short Papers
Disambiguation of biomedical abbreviations
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing
Kernel methods for word sense disambiguation and acronym expansion
AAAI'06 proceedings of the 21st national conference on Artificial intelligence - Volume 2
A discriminative alignment model for abbreviation recognition
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Mining and modeling relations between formal and informal Chinese phrases from web corpora
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Framework for dynamic life critical situations using agents
MATES'09 Proceedings of the 7th German conference on Multiagent system technologies
Disambiguation in the biomedical domain: The role of ambiguity type
Journal of Biomedical Informatics
ICE-TEA: in-context expansion and translation of English abbreviations
CICLing'11 Proceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part II
Using second-order vectors in a knowledge-based method for acronym disambiguation
CoNLL '11 Proceedings of the Fifteenth Conference on Computational Natural Language Learning
A system for adaptive information extraction from highly informal text
NLDB'11 Proceedings of the 16th international conference on Natural language processing and information systems
Artificial Intelligence in Medicine
A hybrid approach to chinese abbreviation expansion
ICCPOL'06 Proceedings of the 21st international conference on Computer Processing of Oriental Languages: beyond the orient: the research challenges ahead
Identification, expansion, and disambiguation of acronyms in biomedical texts
ISPA'05 Proceedings of the 2005 international conference on Parallel and Distributed Processing and Applications
Bootstrapped named entity recognition for product attribute extraction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
A new clustering method for detecting rare senses of abbreviations in clinical notes
Journal of Biomedical Informatics
Learning Abbreviations from Chinese and English Terms by Modeling Non-Local Information
ACM Transactions on Asian Language Information Processing (TALIP)
Mining acronym expansions and their meanings using query click log
Proceedings of the 22nd international conference on World Wide Web
Normalization of informal text
Computer Speech and Language
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Text normalization is an important aspect of successful information retrieval from medical documents such as clinical notes, radiology reports and discharge summaries. In the medical domain, a significant part of the general problem of text normalization is abbreviation and acronym disambiguation. Numerous abbreviations are used routinely throughout such texts and knowing their meaning is critical to data retrieval from the document. In this paper I will demonstrate a method of automatically generating training data for Maximum Entropy (ME) modeling of abbreviations and acronyms and will show that using ME modeling is a promising technique for abbreviation and acronym normalization. I report on the results of an experiment involving training a number of ME models used to normalize abbreviations and acronyms on a sample of 10,000 rheumatology notes with ~89% accuracy.