Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
An Algorithm that Learns What‘s in a Name
Machine Learning - Special issue on natural language learning
A maximum entropy approach to named entity recognition
A maximum entropy approach to named entity recognition
Nymble: a high-performance learning name-finder
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
Named Entity recognition without gazetteers
EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
SRA: description of the SRA system as used for MUC-6
MUC6 '95 Proceedings of the 6th conference on Message understanding
Lattice-based tagging using support vector machines
CIKM '03 Proceedings of the twelfth international conference on Information and knowledge management
TEG: a hybrid approach to information extraction
Proceedings of the thirteenth ACM international conference on Information and knowledge management
Machine learning-based named entity recognition via effective integration of various evidences
Natural Language Engineering
Teaching a weaker classifier: named entity recognition on upper case text
ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Closing the gap: learning-based information extraction rivaling knowledge-engineering methods
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Named entity recognition with a maximum entropy approach
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Named entity recognition using a character-based probabilistic approach
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Secure deletion from inverted indexes on compliance storage
Proceedings of the second ACM workshop on Storage security and survivability
Incorporating non-local information into information extraction systems by Gibbs sampling
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Improving name tagging by reference resolution and relation detection
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
An effective two-stage model for exploiting non-local dependencies in named entity recognition
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Practical use of non-local features for statistical spoken language understanding
Computer Speech and Language
International Journal of Business Intelligence and Data Mining
Adapting svm for data sparseness and imbalance: A case study in information extraction
Natural Language Engineering
The difficulties of taxonomic name extraction and a solution
BioNLP '06 Proceedings of the Workshop on Linking Natural Language Processing and Biology: Towards Deeper Biological Literature Analysis
The difficulties of taxonomic name extraction and a solution
LNLBioNLP '06 Proceedings of the HLT-NAACL BioNLP Workshop on Linking Natural Language and Biology
Context and Domain Knowledge Enhanced Entity Spotting in Informal Text
ISWC '09 Proceedings of the 8th International Semantic Web Conference
CRF-based active learning for Chinese named entity recognition
SMC'09 Proceedings of the 2009 IEEE international conference on Systems, Man and Cybernetics
Fuzzy pattern rule induction for information extraction
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
AI'07 Proceedings of the 20th Australian joint conference on Advances in artificial intelligence
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
Kernel-based reranking for named-entity extraction
COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics: Posters
The REG summarization system with question reformulation at QA@INEX track 2010
INEX'10 Proceedings of the 9th international conference on Initiative for the evaluation of XML retrieval: comparative evaluation of focused retrieval
Passage retrieval for incorporating global evidence in sequence labeling
Proceedings of the 20th ACM international conference on Information and knowledge management
Watch the Story Unfold with TextWheel: Visualization of Large-Scale News Streams
ACM Transactions on Intelligent Systems and Technology (TIST)
Extracting named entities using support vector machines
KDLL'06 Proceedings of the 2006 international conference on Knowledge Discovery in Life Science Literature
A systematic comparison of feature-rich probabilistic classifiers for NER tasks
PKDD'05 Proceedings of the 9th European conference on Principles and Practice of Knowledge Discovery in Databases
Chinese noun phrase metaphor recognition with maximum entropy approach
CICLing'06 Proceedings of the 7th international conference on Computational Linguistics and Intelligent Text Processing
Named entity recognition for web content filtering
NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
A simple rule-based approach to organization name recognition in chinese text
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
SVM based learning system for information extraction
Proceedings of the First international conference on Deterministic and Statistical Methods in Machine Learning
DS'05 Proceedings of the 8th international conference on Discovery Science
Heuristic and rule-based knowledge acquisition: classification of numeral strings in text
PKAW'06 Proceedings of the 9th Pacific Rim Knowledge Acquisition international conference on Advances in Knowledge Acquisition and Management
Comparison of numeral strings interpretation: rule-based and feature-based n-gram methods
AI'06 Proceedings of the 19th Australian joint conference on Artificial Intelligence: advances in Artificial Intelligence
Advances in Artificial Intelligence
Extending enterprise service design knowledge using clustering
ICSOC'12 Proceedings of the 10th international conference on Service-Oriented Computing
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This paper presents a maximum entropy-based named entity recognizer (NER). It differs from previous machine learning-based NERs in that it uses information from the whole document to classify each word, with just one classifier. Previous work that involves the gathering of information from the whole document often uses a secondary classifier, which corrects the mistakes of a primary sentence-based classifier. In this paper, we show that the maximum entropy framework is able to make use of global information directly, and achieves performance that is comparable to the best previous machine learning-based NERs on MUC-6 and MUC-7 test data.