Inducing Features of Random Fields
IEEE Transactions on Pattern Analysis and Machine Intelligence
Learning dictionaries for information extraction by multi-level bootstrapping
AAAI '99/IAAI '99 Proceedings of the sixteenth national conference on Artificial intelligence and the eleventh Innovative applications of artificial intelligence conference innovative applications of artificial intelligence
Conditional Random Fields: Probabilistic Models for Segmenting and Labeling Sequence Data
ICML '01 Proceedings of the Eighteenth 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
Table extraction using conditional random fields
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Layout and language: integrating spatial and linguistic knowledge for layout understanding tasks
COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
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
Biomedical named entity recognition using conditional random fields and rich feature sets
JNLPBA '04 Proceedings of the International Joint Workshop on Natural Language Processing in Biomedicine and its Applications
Towards a comprehensive call ontology for Research 2.0
i-KNOW '11 Proceedings of the 11th International Conference on Knowledge Management and Knowledge Technologies
Speculative originality and optimality in knowledge development infrastructures
Proceedings of the 2012 iConference
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For members of the research community it is vital to stay informed about conferences, workshops, and other research meetings relevant to their field. These events are typically announced in calls for papers (CFPs) that are distributed via mailing lists. We employ Conditional Random Fields for the task of extracting key information such as conference names, titles, dates, locations and submission deadlines from CFPs. Extracting this information from CFPs automatically has applications in building automated conference calendars and search engines for CFPs. We combine a variety of features, including generic token classes, domain-specific dictionaries and layout features. Layout features prove particularly useful in the absence of grammatical structure, improving average F1 by 30% in our experiments.