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Foundations of statistical natural language processing
Foundations of statistical natural language processing
Machine Learning for Information Extraction in Informal Domains
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Maximum Entropy Markov Models for Information Extraction and Segmentation
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Constructing Biological Knowledge Bases by Extracting Information from Text Sources
Proceedings of the Seventh International Conference on Intelligent Systems for Molecular Biology
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ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Statistical decision-tree models for parsing
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ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
A fully statistical approach to natural language interfaces
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
Induction of first-order decision lists: results on learning the past tense of English verbs
Journal of Artificial Intelligence Research
Adaptive information extraction from text by rule induction and generalisation
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Relational learning via propositional algorithms: an information extraction case study
IJCAI'01 Proceedings of the 17th international joint conference on Artificial intelligence - Volume 2
Representing sentence structure in hidden Markov models for information extraction
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CRYSTAL inducing a conceptual dictionary
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ACM SIGKDD Explorations Newsletter
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WI '04 Proceedings of the 2004 IEEE/WIC/ACM International Conference on Web Intelligence
Editorial: special issue on web content mining
ACM SIGKDD Explorations Newsletter
ACM SIGKDD Explorations Newsletter
Gimme' the context: context-driven automatic semantic annotation with C-PANKOW
WWW '05 Proceedings of the 14th international conference on World Wide Web
Mining knowledge from text using information extraction
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Adapting Web information extraction knowledge via mining site-invariant and site-dependent features
ACM Transactions on Internet Technology (TOIT)
Combining Information Extraction Systems Using Voting and Stacked Generalization
The Journal of Machine Learning Research
Hierarchical rule generalisation for speaker identification in fiction books
SAICSIT '06 Proceedings of the 2006 annual research conference of the South African institute of computer scientists and information technologists on IT research in developing countries
Webpage understanding: an integrated approach
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Ontology learning: state of the art and open issues
Information Technology and Management
Mining and analysing scale-free protein protein interaction network
International Journal of Bioinformatics Research and Applications
Heuristic learning of rules for information extraction from web documents
Proceedings of the 2nd international conference on Scalable information systems
Extracting Semantic Frames from Thai Medical-Symptom Phrases with Unknown Boundaries
ASWC '08 Proceedings of the 3rd Asian Semantic Web Conference on The Semantic Web
Multiagent Incremental Learning in Networks
PRIMA '08 Proceedings of the 11th Pacific Rim International Conference on Multi-Agents: Intelligent Agents and Multi-Agent Systems
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A probabilistic classification approach for lexical textual entailment
AAAI'05 Proceedings of the 20th national conference on Artificial intelligence - Volume 3
Learning in a Fixed or Evolving Network of Agents
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 02
A unified model of phrasal and sentential evidence for information extraction
EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Proceedings of the 2010 conference on New Trends in Software Methodologies, Tools and Techniques: Proceedings of the 9th SoMeT_10
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Journal of Artificial Intelligence Research
Extracting chemical reactions from Thai text for semantics-based information retrieval
ACIIDS'10 Proceedings of the Second international conference on Intelligent information and database systems: Part I
Automatic rule learning exploiting morphological features for named entity recognition in Turkish
Journal of Information Science
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HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
Mining the semantics of text via counter-training
EPIA'05 Proceedings of the 12th Portuguese conference on Progress in Artificial Intelligence
Learning information extraction rules for protein annotation from unannotated corpora
CICLing'05 Proceedings of the 6th international conference on Computational Linguistics and Intelligent Text Processing
An overview and classification of adaptive approaches to information extraction
Journal on Data Semantics IV
Ontology enrichment through automatic semantic annotation of on-line glossaries
EKAW'06 Proceedings of the 15th international conference on Managing Knowledge in a World of Networks
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Information Processing and Management: an International Journal
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Discriminative learning for joint template filling
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TEX: An efficient and effective unsupervised Web information extractor
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Engineering Applications of Artificial Intelligence
Enhancing search: events and their discourse context
CICLing'13 Proceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 2
SEED: a framework for extracting social events from press news
Proceedings of the 22nd international conference on World Wide Web companion
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Information extraction is a form of shallow text processing that locates a specified set of relevant items in a natural-language document. Systems for this task require significant domain-specific knowledge and are time-consuming and difficult to build by hand, making them a good application for machine learning. We present an algorithm, RAPIER, that uses pairs of sample documents and filled templates to induce pattern-match rules that directly extract fillers for the slots in the template. RAPIER is a bottom-up learning algorithm that incorporates techniques from several inductive logic programming systems. We have implemented the algorithm in a system that allows patterns to have constraints on the words, part-of-speech tags, and semantic classes present in the filler and the surrounding text. We present encouraging experimental results on two domains.