Machine Learning
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
Explorations in Automatic Thesaurus Discovery
Explorations in Automatic Thesaurus Discovery
Automatic acquisition of hyponyms from large text corpora
COLING '92 Proceedings of the 14th conference on Computational linguistics - Volume 2
Weakly supervised natural language learning without redundant views
NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Counter-training in discovery of semantic patterns
ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
A bootstrapping method for learning semantic lexicons using extraction pattern contexts
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
Learning subjective nouns using extraction pattern bootstrapping
CONLL '03 Proceedings of the seventh conference on Natural language learning at HLT-NAACL 2003 - Volume 4
Names and similarities on the web: fact extraction in the fast lane
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
Bootstrapping without the boot
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Integrating pattern-based and distributional similarity methods for lexical entailment acquisition
COLING-ACL '06 Proceedings of the COLING/ACL on Main conference poster sessions
Graph-based analysis of semantic drift in Espresso-like bootstrapping algorithms
EMNLP '08 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Tools to address the interdependence between tokenisation and standoff annotation
NLPXML '06 Proceedings of the 5th Workshop on NLP and XML: Multi-Dimensional Markup in Natural Language Processing
Inducing domain-specific semantic class taggers from (almost) nothing
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
On learning subtypes of the part-whole relation: do not mix your seeds
ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
Unsupervised discovery of negative categories in lexicon bootstrapping
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
TSD'10 Proceedings of the 13th international conference on Text, speech and dialogue
Burning up: finding fever expressions in triage notes
Proceedings of the 73rd ASIS&T Annual Meeting on Navigating Streams in an Information Ecosystem - Volume 47
HITS-based seed selection and stop list construction for bootstrapping
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
Relation guided bootstrapping of semantic lexicons
HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies: short papers - Volume 2
The role of information extraction in the design of a document triage application for biocuration
BioNLP '11 Proceedings of BioNLP 2011 Workshop
Large-scale noun compound interpretation using bootstrapping and the web as a corpus
EMNLP '11 Proceedings of the Conference on Empirical Methods in Natural Language Processing
Ensemble-based semantic lexicon induction for semantic tagging
SemEval '12 Proceedings of the First Joint Conference on Lexical and Computational Semantics - Volume 1: Proceedings of the main conference and the shared task, and Volume 2: Proceedings of the Sixth International Workshop on Semantic Evaluation
Bootstrapping biomedical ontologies for scientific text using NELL
BioNLP '12 Proceedings of the 2012 Workshop on Biomedical Natural Language Processing
Data & Knowledge Engineering
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Iterative bootstrapping algorithms are typically compared using a single set of hand-picked seeds. However, we demonstrate that performance varies greatly depending on these seeds, and favourable seeds for one algorithm can perform very poorly with others, making comparisons unreliable. We exploit this wide variation with bagging, sampling from automatically extracted seeds to reduce semantic drift. However, semantic drift still occurs in later iterations. We propose an integrated distributional similarity filter to identify and censor potential semantic drifts, ensuring over 10% higher precision when extracting large semantic lexicons.