A tutorial on hidden Markov models and selected applications in speech recognition
Readings in speech recognition
Representations of quasi-Newton matrices and their use in limited memory methods
Mathematical Programming: Series A and B
Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
A decision-theoretic generalization of on-line learning and an application to boosting
Journal of Computer and System Sciences - Special issue: 26th annual ACM symposium on the theory of computing & STOC'94, May 23–25, 1994, and second annual Europe an conference on computational learning theory (EuroCOLT'95), March 13–15, 1995
Statistical Models for Text Segmentation
Machine Learning - Special issue on natural language learning
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth International Conference on Machine Learning
An Alternate Objective Function for Markovian Fields
ICML '02 Proceedings of the Nineteenth International Conference on Machine Learning
Maximum Entropy Markov Models for Information Extraction and Segmentation
ICML '00 Proceedings of the Seventeenth International Conference on Machine Learning
Text chunking based on a generalization of winnow
The Journal of Machine Learning Research
Shallow parsing with conditional random fields
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
A comparison of algorithms for maximum entropy parameter estimation
COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
Discriminative probabilistic models for relational data
UAI'02 Proceedings of the Eighteenth conference on Uncertainty in artificial intelligence
Sequence Modeling with Mixtures of Conditional Maximum Entropy Distributions
ICDM '03 Proceedings of the Third IEEE International Conference on Data Mining
ACM Transactions on Asian Language Information Processing (TALIP)
Web-scale information extraction in knowitall: (preliminary results)
Proceedings of the 13th international conference on World Wide Web
Kernel conditional random fields: representation and clique selection
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Robust feature induction for support vector machines
ICML '04 Proceedings of the twenty-first international conference on Machine learning
Training conditional random fields via gradient tree boosting
ICML '04 Proceedings of the twenty-first international conference on Machine learning
UAI '04 Proceedings of the 20th conference on Uncertainty in artificial intelligence
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
Improving discriminative sequential learning with rare--but--important associations
Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining
Unsupervised named-entity extraction from the web: an experimental study
Artificial Intelligence
Collective multi-label classification
Proceedings of the 14th ACM international conference on Information and knowledge management
Learning the structure of Markov logic networks
ICML '05 Proceedings of the 22nd international conference on Machine learning
Discriminatively Trained Markov Model for Sequence Classification
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Discriminative Reranking for Natural Language Parsing
Computational Linguistics
Information extraction from research papers using conditional random fields
Information Processing and Management: an International Journal
Using conditional random fields to predict pitch accents in conversational speech
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Scaling conditional random fields using error-correcting codes
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Logarithmic opinion pools for conditional random fields
ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Segment-based hidden Markov models for information extraction
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Identifying sources of opinions with conditional random fields and extraction patterns
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Part-of-speech tagging using virtual evidence and negative training
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Corrective feedback and persistent learning for information extraction
Artificial Intelligence
Conditional models for contextual human motion recognition
Computer Vision and Image Understanding - Special issue on modeling people: Vision-based understanding of a person's shape, appearance, movement, and behaviour
Soft pattern matching models for definitional question answering
ACM Transactions on Information Systems (TOIS)
Extracting Places and Activities from GPS Traces Using Hierarchical Conditional Random Fields
International Journal of Robotics Research
Improving discriminative sequential learning by discovering important association of statistics
ACM Transactions on Asian Language Information Processing (TALIP)
Extraction and search of chemical formulae in text documents on the web
Proceedings of the 16th international conference on World Wide Web
Learning Factor Graphs in Polynomial Time and Sample Complexity
The Journal of Machine Learning Research
Relational Dependency Networks
The Journal of Machine Learning Research
Detecting anomalies in network traffic using maximum entropy estimation
IMC '05 Proceedings of the 5th ACM SIGCOMM conference on Internet Measurement
Exploiting non-local features for spoken language understanding
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Domain-constrained semi-supervised mining of tracking models in sensor networks
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Practical use of non-local features for statistical spoken language understanding
Computer Speech and Language
Automatic feature selection in the markov random field model for information retrieval
Proceedings of the sixteenth ACM conference on Conference on information and knowledge management
Open information extraction from the web
Communications of the ACM - Surviving the data deluge
Identifying table boundaries in digital documents via sparse line detection
Proceedings of the 17th ACM conference on Information and knowledge management
StatSnowball: a statistical approach to extracting entity relationships
Proceedings of the 18th international conference on World wide web
A Simple and Efficient Model Pruning Method for Conditional Random Fields
ICCPOL '09 Proceedings of the 22nd International Conference on Computer Processing of Oriental Languages. Language Technology for the Knowledge-based Economy
Structure Learning of Markov Logic Networks through Iterated Local Search
Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
Context-aware query classification
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Tunable domain-independent event extraction in the MIRA framework
BioNLP '09 Proceedings of the Workshop on Current Trends in Biomedical Natural Language Processing: Shared Task
Methods for domain-independent information extraction from the web: an experimental comparison
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Interactive information extraction with constrained conditional random fields
AAAI'04 Proceedings of the 19th national conference on Artifical intelligence
Competitive generative models with structure learning for NLP classification tasks
EMNLP '06 Proceedings of the 2006 Conference on Empirical Methods in Natural Language Processing
Discriminative training of Markov logic networks
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 2
CRF-OPT: an efficient high-quality conditional random field solver
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
Structure learning on large scale common sense statistical models of human state
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Feature selection for activity recognition in multi-robot domains
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 3
Quadratic features and deep architectures for chunking
NAACL-Short '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Companion Volume: Short Papers
Word sense disambiguation through sememe labeling
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Training conditional random fields using virtual evidence boosting
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
Drinking activity analysis from fast food eating video using generative models
CEA '09 Proceedings of the ACM multimedia 2009 workshop on Multimedia for cooking and eating activities
Efficient Markov network structure discovery using independence tests
Journal of Artificial Intelligence Research
Enhanced interactive question-answering with conditional random fields
IQA '06 Proceedings of the Interactive Question Answering Workshop at HLT-NAACL 2006
Unsupervised named-entity extraction from the Web: An experimental study
Artificial Intelligence
Corrective feedback and persistent learning for information extraction
Artificial Intelligence
An integrated framework for de-identifying unstructured medical data
Data & Knowledge Engineering
Automatic link detection: a sequence labeling approach
Proceedings of the 18th ACM conference on Information and knowledge management
Selecting features of linear-chain conditional random fields via greedy stage-wise algorithms
Pattern Recognition Letters
Probabilistic inductive logic programming
Extracting compiler provenance from program binaries
Proceedings of the 9th ACM SIGPLAN-SIGSOFT workshop on Program analysis for software tools and engineering
Analysis of a probabilistic model of redundancy in unsupervised information extraction
Artificial Intelligence
Grafting-light: fast, incremental feature selection and structure learning of Markov random fields
Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
A joint model for normalizing gene and organism mentions in text
WBIE '09 Proceedings of the Workshop on Biomedical Information Extraction
Concensus of self-features for nonverbal behavior analysis
HBU'10 Proceedings of the First international conference on Human behavior understanding
Discriminative graphical models for faculty homepage discovery
Information Retrieval
Frequent words' grammar information in Chinese chunking
ISICA'10 Proceedings of the 5th international conference on Advances in computation and intelligence
Inferring user search intention based on situation analysis of the physical world
UIC'10 Proceedings of the 7th international conference on Ubiquitous intelligence and computing
IEEE/ACM Transactions on Computational Biology and Bioinformatics (TCBB)
Boosting learning and inference in Markov logic through metaheuristics
Applied Intelligence
Resource Allocation via Message Passing
INFORMS Journal on Computing
A linear-chain CRF-based learning approach for web opinion mining
WISE'10 Proceedings of the 11th international conference on Web information systems engineering
Recovering the toolchain provenance of binary code
Proceedings of the 2011 International Symposium on Software Testing and Analysis
An efficient pre-processing method to identify logical components from PDF documents
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Enhancing activity recognition in smart homes using feature induction
DaWaK'11 Proceedings of the 13th international conference on Data warehousing and knowledge discovery
Online structure learning for Markov logic networks
ECML PKDD'11 Proceedings of the 2011 European conference on Machine learning and knowledge discovery in databases - Volume Part II
Constraint propagation for efficient inference in Markov logic
CP'11 Proceedings of the 17th international conference on Principles and practice of constraint programming
Segmenting and labeling query sequences in a multidatabase environment
OTM'11 Proceedings of the 2011th Confederated international conference on On the move to meaningful internet systems - Volume Part I
TildeCRF: conditional random fields for logical sequences
ECML'06 Proceedings of the 17th European conference on Machine Learning
Discovering links between lexical and surface features in questions and answers
WebKDD'04 Proceedings of the 6th international conference on Knowledge Discovery on the Web: advances in Web Mining and Web Usage Analysis
EuroGP'06 Proceedings of the 2006 international conference on Applications of Evolutionary Computing
Training conditional random fields with unlabeled data and limited number of labeled examples
ICMLC'05 Proceedings of the 4th international conference on Advances in Machine Learning and Cybernetics
Hypotheses selection criteria in a reranking framework for spoken language understanding
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Structured sparsity in structured prediction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Bootstrapped named entity recognition for product attribute extraction
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
REV: extracting entity relations from world wide web
Proceedings of the 6th International Conference on Ubiquitous Information Management and Communication
Variational conditional random fields for online speaker detection and tracking
Speech Communication
PROBABILISTIC MODELS FOR FOCUSED WEB CRAWLING
Computational Intelligence
Blinking-based live face detection using conditional random fields
ICB'07 Proceedings of the 2007 international conference on Advances in Biometrics
Resource Allocation via Message Passing
INFORMS Journal on Computing
A joint classification method to integrate scientific and social networks
ECIR'13 Proceedings of the 35th European conference on Advances in Information Retrieval
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Conditional Random Fields (CRFs) are undirected graphical models, a special case of which correspond to conditionally-trained finite state machines. A key advantage of CRFs is their great flexibility to include a wide variety of arbitrary, non-independent features of the input. Faced with this freedom, however, an important question remains: what features should be used? This paper presents an efficient feature induction method for CRFs. The method is founded on the principle of iteratively constructing feature conjunctions that would significantly increase conditional log-likelihood if added to the model. Automated feature induction enables not only improved accuracy and dramatic reduction in parameter count, but also the use of larger cliques, and more freedom to liberally hypothesize atomic input variables that may be relevant to a task. The method applies to linear-chain CRFs, as well as to more arbitrary CRF structures, such as Relational Markov Networks, where it corresponds to learning clique templates, and can also be understood as supervised structure learning. Experimental results on named entity extraction and noun phrase segmentation tasks are presented.