Who Cited It

Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data

2001 · ScholarlyCommons (University of Pennsylvania) · 12,994 citations · 33 from inside this corpus

John Lafferty, Andrew McCallum, Fernando C. N. Pereira low

The source holds an abstract for this work, but its best open-access copy is under no open licence, which does not permit us to republish the text. Read it at the source below.

Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data (2001)Conditional Random Fields: Pr…Foundations of statistical natural language processing (1999)Foundations of statistical na…A maximum entropy approach to natural language processing (1996)A maximum entropy approach to…Transformation-based error-driven learning and natural language processing: a case study … (1995)Transformation-based error-dr…Anomaly detection (2009)Anomaly detectionThe Graph Neural Network Model (2008)The Graph Neural Network ModelOpinion Mining and Sentiment Analysis (2008)Opinion Mining and Sentiment …Large-Scale Machine Learning with Stochastic Gradient Descent (2010)Large-Scale Machine Learning …Connectionist temporal classification (2006)Connectionist temporal classi…Natural Language Processing (almost) from Scratch (2011)Natural Language Processing (…Active Learning Literature Survey (2009)Active Learning Literature Su…Neural Architectures for Named Entity Recognition (2016)Neural Architectures for Name…Natural Language Processing (almost) from Scratch (2011)Natural Language Processing (…Sentiment Analysis and Opinion Mining (2017)Sentiment Analysis and Opinio…Bidirectional LSTM-CRF Models for Sequence Tagging (2015)Bidirectional LSTM-CRF Models…Sentiment analysis algorithms and applications: A survey (2014)Sentiment analysis algorithms…Understanding Machine Learning: From Theory To Algorithms (2015)Understanding Machine Learnin…Incorporating non-local information into information extraction systems by Gibbs sampling (2005)Incorporating non-local infor…Feature-rich part-of-speech tagging with a cyclic dependency network (2003)Feature-rich part-of-speech t…Twitter as a Corpus for Sentiment Analysis and Opinion Mining (2010)Twitter as a Corpus for Senti…Dynamic bayesian networks: representation, inference and learning (2002)Dynamic bayesian networks: re…End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF (2016)End-to-end Sequence Labeling …Conditional Random Fields as Recurrent Neural Networks (2015)Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing (2021)Domain-Specific Language Mode…Maximum Entropy Inverse Reinforcement Learning (2018)Maximum Entropy Inverse Reinf…Natural language processing: an introduction (2011)Natural language processing: …Large Margin Methods for Structured and Interdependent Output Variables (2005)Large Margin Methods for Stru…Stochastic Gradient Descent Tricks (2012)Stochastic Gradient Descent T…Discriminative training methods for hidden Markov models (2002)Discriminative training metho…Head-Driven Statistical Models for Natural Language Parsing (2003)Head-Driven Statistical Model…Deep Contextualized Word Representations (2018)Deep Contextualized Word Repr…The text mining handbook: advanced approaches in analyzing unstructured data (2007)The text mining handbook: adv…Opinion observer (2005)Opinion observerSentiment Analysis and Subjectivity (2010)Sentiment Analysis and Subjec…A Survey on Deep Learning for Named Entity Recognition (2020)A Survey on Deep Learning for…Techniques and applications for sentiment analysis (2013)Techniques and applications f…Design challenges and misconceptions in named entity recognition (2009)Design challenges and misconc…
36 of 36 neighbouring works in this corpus. Blue is what this paper cites; orange is what cites it, and a dashed line is one neighbour citing another. Only the largest labels are drawn — every node carries its full title on hover.
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What this paper cites, inside the corpus

PaperYearCited
Foundations of statistical natural language processing19999,997
A maximum entropy approach to natural language processing19963,129
Transformation-based error-driven learning and natural language processing: a case study …19951,535

What cites it, inside the corpus

PaperYearCited
Anomaly detection200911,511
The Graph Neural Network Model20089,662
Opinion Mining and Sentiment Analysis20086,837
Large-Scale Machine Learning with Stochastic Gradient Descent20105,695
Connectionist temporal classification20065,582
Natural Language Processing (almost) from Scratch20115,174
Active Learning Literature Survey20094,788
Neural Architectures for Named Entity Recognition20164,482
Natural Language Processing (almost) from Scratch20113,991
Sentiment Analysis and Opinion Mining20173,331
Bidirectional LSTM-CRF Models for Sequence Tagging20153,287
Sentiment analysis algorithms and applications: A survey20143,264
Understanding Machine Learning: From Theory To Algorithms20153,081
Incorporating non-local information into information extraction systems by Gibbs sampling20053,044
Feature-rich part-of-speech tagging with a cyclic dependency network20032,885
Twitter as a Corpus for Sentiment Analysis and Opinion Mining20102,719
Dynamic bayesian networks: representation, inference and learning20022,604
End-to-end Sequence Labeling via Bi-directional LSTM-CNNs-CRF20162,595
Conditional Random Fields as Recurrent Neural Networks20152,437
Domain-Specific Language Model Pretraining for Biomedical Natural Language Processing20212,146
Maximum Entropy Inverse Reinforcement Learning20182,055
Natural language processing: an introduction20112,014
Large Margin Methods for Structured and Interdependent Output Variables20051,957
Stochastic Gradient Descent Tricks20121,944
Discriminative training methods for hidden Markov models20021,895
Head-Driven Statistical Models for Natural Language Parsing20031,861
Deep Contextualized Word Representations20181,783
The text mining handbook: advanced approaches in analyzing unstructured data20071,626
Opinion observer20051,609
Sentiment Analysis and Subjectivity20101,593
A Survey on Deep Learning for Named Entity Recognition20201,534
Techniques and applications for sentiment analysis20131,509
Design challenges and misconceptions in named entity recognition20091,491

Links

Open access copy · OpenAlex record

Topics

Natural Language Processing TechniquesComputer Science
Algorithms and Data CompressionComputer Science
Speech Recognition and SynthesisComputer Science

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complete

Nothing in this record contradicts itself and no field we check is missing.

  • supports3 author record(s) attached.
  • supports24 reference(s) recorded.
  • neutralThe DOI carries no year to check against.
  • supportsA title is present.

Provenance

Everything above was read from one stored OpenAlex payload, fetched 2026-09-04T03:58:40+00:00.

sha256 7e3d99a592f7f61f…