Semi-Supervised Named Entity Recognition: Learning to Recognize 100 Entity Types with Little Supervision

Semi-Supervised Named Entity Recognition: Learning to Recognize 100 Entity Types with Little Supervision

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by David Nadeau

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4 - 0 self

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@MISC{Nadeau_semi-supervisednamed,
    author = {David Nadeau},
    title = {Semi-Supervised Named Entity Recognition: Learning to Recognize 100 Entity Types with Little Supervision},
    year = {}
}

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Abstract

Table of contents List of tables........................................................................................................................ iv List of figures....................................................................................................................... v Abstract............................................................................................................................... vi

Citations

2215	Data Mining: Practical machine learning tools and techniques. 2nd edition - Witten, Frank - 2005
800	Fast effective rule induction - Cohen - 1995
764	S.: A solution to plato’s problem: The latent semantic analysis theory of acquisition, induction and representation of knowledge. Psychological Review 104 - Landauer, Dumais - 1997
673	Automatic Acquisition of Hyponyms from Large Text Corpora - Hearst - 1992
528	Automatic retrieval and clustering of similar words - Lin - 1998
385	Naming and Necessity - Kripke - 1980
381	GATE: A framework and graphical development environment for robust NLP tools and applications - Cunningham, Maynard, et al. - 2002
381	Estimating the support of a high-dimensional distribution - Schölkopf, Platt, et al. - 2001
359	Unsupervised models for named entity classification - Collins, Singer - 1999
283	Extracting patterns and relations from the world wide web - Brin - 1998
238	Nymble: a High-Performance Learning Name-finder - Bikel, Miller, et al. - 1997
205	Unsupervised named-entity extraction from the web: an experimental study - Etzioni, Cafarella, et al. - 2005
178	Message Understanding Conference - 6: A brief history - Grishman, Sundheim - 1996
175	Kegelmeyer W: SMOTE: Synthetic Minority Over-sampling Technique - Chawla, Bowyer, et al.
116	Early results for named entity recognition with conditional random fields, feature induction and web-enhanced lexicons - McCallum, Li - 2003
116	MA: A Simple Algorithm For Identifying Abbreviation Definitions in Biomedical Text - AS, Hearst
101	Named entity recognition without gazetteers - Mikheev, Moens, et al. - 1999
90	Unsupervised personal name disambiguation - Mann, Yarowsky - 2003
87	Data Mining for Direct Marketing: Problems and Solutions - CX, Li - 1998
87	Introduction to the conll-2003 shared task: Languageindependent named entity recognition - Sang, Meulder - 2003
81	Language Independent Named Entity Recognition Combining Morphological and Contextual Evidence - Cucerzan, Yarowsky - 1999
71	A probabilistic model of redundancy in information extraction - Downey, Etzioni, et al. - 2005
67	Robin Classification - Furnkranz, Round
65	Minorthird: Methods for identifying names and ontological relations in text using heuristics for inducing regularities from data. http://minorthird.sourceforge.net - Cohen - 2004
64	Frequency estimates for statistical word similarity measures - Terra, Clarke - 2003
61	Named Entity Recognition through Classifier Combination - Florian, Ittycheriah, et al. - 2003
60	Ranking algorithms for named-entity extraction: Boosting and the voted perceptron - Collins - 2002
59	Biomedical Named Entity Recognition Using Conditional Random Fields and Rich Feature Sets - Settles
56	Schütze H, Altman R: Creating an Online Dictionary of Abbreviations from MEDLINE - Chang
56	Exploiting dictionaries in named entity extraction: combining semi-Markov extraction processes and data integration methods - Cohen, Sarawagi - 2004
54	A Pattern Matching Method for Finding Noun and Proper Noun Translations from Noisy Parallel Corpora - Fung - 1995
54	Information extraction supported question answering - Srihari - 1999
53	Mining the web for synonyms - Turney
48	JD: The GENIA Corpus: an Annotated Research Abstract - Ohta, Tateisi, et al.
46	P: Building text classifiers using positive and unlabeled examples - Liu, Dai, et al.
44	Overview of MUC-7/MET-2 - Chinchor - 1998
42	Induction of semantic classes from natural language text - Lin, Pantel - 2001
36	Vijay-Shanker K: A Biological Named Entity Recognizer - Narayanaswamy, KE
36	Measuring semantic similarity by latent relational analysis - Turney - 2005
35	Learning Page-independent Heuristics for Extracting Data from the Web. accepted for WWW-99 - Cohen, Fan
35	Recognizing acronyms and their definitions - Taghva, Gilbreth - 1995
33	Named entity recognition from diverse text types - Maynard, Tablan, et al. - 2001
33	A survey of named entity recognition and classification. Linguisticae Investigationes - Nadeau, Sekine - 2007
30	Tagging Romanian texts: a case study for QTAG, a language independent probabilistic tagger - Tufis, Mason - 1998
29	Towards large-scale, open-domain and ontologybased named entity classification - Cimiano, Volker - 2005
29	Extracting personal names from email: Applying named entity recognition to informal text - Minkov, Wang, et al. - 2005
29	Hybrid text mining for finding abbreviations and their definitions - Park, Byrd - 2001
28	Learning to match and cluster entity names - Cohen, Richman - 2002
27	Mapping abbreviations to full forms in biomedical articles - Hong, Hripcsak, et al. - 2002
26	Identification and tracing of ambiguous names: Discriminative and generative approaches - Li, Morie, et al. - 2004