Eugene Charniak

0 Comments Leave a Comment

1-14 of 14
Categories:
Default: Discourse, Entailment, Machine Translation, NER, Parsing, Segmentation, Semantic, Sentiment, Summarization, WSD

About Eugene Charniak

Eugene Charniak is a Computer Science and Cognitive Science professor at Brown University. He has an A.B. in Physics from The University of Chicago and a Ph.D. from M.I.T. in Computer Science. His research has always been in the area of language understanding or technologies which relate to it, such as knowledge representation, reasoning under uncertainty, and learning. Over the last few years he has been interested in statistical techniques for language understanding. His research in this area has included work in the subareas of part-of-speech tagging, probabilistic context-free grammar induction, and, more recently, syntactic disambiguation through word statistics, efficient syntactic parsing, and lexical resource acquisition through statistical means.

Read More


He is a Fellow of the American Association of Artificial Intelligence and was previously a Councilor of the organization.

He has published four books:

# Statistical Language Learning, Cambridge: MIT Press (1993)
# Introduction to Artificial Intelligence (with Drew McDermott), Reading MA: Addison-Wesley (1985)
# Artificial Intelligence Programming (now in a second edition) (with Chris Riesbeck, Drew McDermott, and James Meehan), Hillsdale NJ: Lawrence Erlbaum Associates (1980, 1987)
# Computational Semantics, (with Yorick Wilks), Amsterdam: North-Holland (1976)

= External links =
* [http://www.cs.brown.edu/people/ec/ Eugene Charniak's homepage at Brown University]"

  1. Mentioned In 14 Articles

  2. Parsing to Stanford Dependencies: Trade-offs between speed and accuracy

    Explore Article nlp.stanford.edu (Apr 4 2010) Parsing

    ...ngs of the ACL-PASCAL Workshop on Textual Entailment and Paraphrasing, pages 101–106, Prague, June. Eugene Charniak and Mark Johnson. 2005. Coarse-to-fine n-best parsing and maxent discriminative reranking. In Procee... (Read Full Article)

    Comment on Article Mentions:   Association for Computational Linguistics   Yoram Singer   Manning

  3. The Stanford typed dependencies representation

    Explore Article www-nlp.stanford.edu (Aug 19 2009) Machine Translation

    ...roceedings of the 41st Meeting of the Association for Computational Linguistics. Lease, Matthew and Eugene Charniak. 2005. Parsing biomedical literature. In Proceedings of the Second International Joint Conference o... (Read Full Article)

    Comment on Article Mentions:   Association for Computational Linguistics   Christopher Manning   Los Angeles

  4. Sentence realization model for a natural language generation system

    Explore Article PatFT » Page 1 of 1 (Apr 28 2009) Machine Translation , Summarization

    ...s in the parsing process.Examples of such parsing models are set out in the following publications. Eugene Charniak, "A Maximum-Entropy-Inspired Parser", appearing in the Proceedings of NAACL-2000, Seattle, Wash., p... (Read Full Article)

    Comment on Article Mentions:   Association for Computational Linguistics   K. Knight   Japan

  5. The Stanford typed dependencies representation

    Explore Article nlp.stanford.edu (Aug 7 2008) Machine Translation , Parsing

    ...roceedings of the 41st Meeting of the Association for Computational Linguistics. Lease, Matthew and Eugene Charniak. 2005. Parsing biomedical literature. In Proceedings of the Second International Joint Conference o... (Read Full Article)

    Comment on Article Mentions:   Association for Computational Linguistics   Patrick Pantel   Tapio Salakoski

  6. One-row keyboard and approximate typing

    Explore Article PatFT » Page 1 of 1 (Jun 17 2008) Machine Translation , WSD

    ...om/booksearch/isbnInquiry.asp?userid=3B6Dv2- 7AZ1&isbn;=140202293X&itm;=136. [15] Glenn Carroll and Eugene Charniak. Two experiments on learning probabilistic dependencygrammars from corpora. Technical Report CS-92-... (Read Full Article)

    Comment on Article Mentions:   Association for Computational Linguistics   sub   Fernando Pereira

  7. Linguistically informed statistical models of constituent structure for ordering in sentence realization for a natural language generation system

    Explore Article PatFT » Page 1 of 1 (Mar 18 2008) Machine Translation , Parsing

    ...g the generation process.Examples of such parsing models are set out in the following publications. Eugene Charniak, "A Maximum-Entropy-Inspired Parser", appearing in The Proceedings of NAACL-2000, Seattle, Wash., p... (Read Full Article)

    Comment on Article Mentions:   Association for Computational Linguistics   Japan   AI Magazine

  8. Discriminative Syntactic Language Modeling for Speech Recognition.

    Explore Article CSAIL People (Dec 27 2007) Machine Translation , Parsing

    Discriminative Syntactic Language Modeling for Speech Recognition Michael Collins MIT CSAIL mcollins@csail.mit.edu Brian Roark OGI/OHSU roark@cslu.ogi.edu Murat Saraclar Bogazici University murat.saraclar@boun.edu.tr Abstract We describe a method for discriminative training of a language model that makes use of syntactic features. We follow a reranking approach, where a baseline recogniser is used to produce 1000-best output for each acoustic input, and a second “reranking” model is then used (Read Full Article)

    Comment on Article Mentions:   Libin Shen   Emnlp   Penn Treebank

  9. Hidden-Variable Models for Discriminative Reranking.

    Explore Article CSAIL People (Dec 27 2007) Machine Translation , Parsing

    ...er. 1992. Class–based n– gram models of natural language. Computational Linguistics, 18(4):467–479. Eugene Charniak and Mark Johnson. 2005. Coarse–to–fine n– best parsing and maxent discriminative reranking. In Proce... (Read Full Article)

    Comment on Article Mentions:   Regina Barzilay   Lillian Lee   Ronald M. Kaplan

  10. Morphology and Reranking for the Statistical Parsing of Spanish.

    Explore Article CSAIL People (Dec 27 2007) Parsing

    Morphology and Reranking for the Statistical Parsing of Spanish Brooke Cowan MIT CSAIL brooke@csail.mit.edu Abstract We present two methods for incorporating detailed features in a Spanish parser, building on a baseline model that is a lexicalized PCFG. The first method exploits Spanish morphology, and achieves an F1 constituency score of 83.6%. This is an improvement over 81.2% accuracy for the baseline, which makes little or no use of morphological information. ... (Read Full Article)

    Comment on Article Mentions:   Roger Levy   Peter Bartlett   Ann Arbor

  11. Modeling Local Coherence: An Entity-Based Approach

    Explore Article CSAIL People (Dec 18 2007) Discourse

    This paper considers the problem of automatic assessment of local coherence. We present a novel entity-based representation of discourse which is inspired by Centering Theory and can be computed automatically from raw text. (Read Full Article)

    Comment on Article Mentions:   Associated Press   D. Manning   Hlt-Naacl

  12. Inducing Temporal Graphs

    Explore Article CSAIL People (Dec 18 2007) Segmentation

    We consider the problem of constructing a directed acyclic graph that encodes temporal relations found in a text. The unit of our analysis is a temporal segment, a fragment of text that maintains temporal coherence. The strength of our approach lies in its ability to simultane... (Read Full Article)

    Comment on Article Mentions:   Patrick Hanks   Hearst   Intel Xeon

  13. Apparatus and method for generating a summary according to hierarchical structure of topic

    Explore Article PatFT » Page 1 of 1 (Nov 8 2005) Summarization

    ...propriety of a series of words using appearanceprobability estimated by training data is reported, (Eugene Charniak, "Hidden Markov and Two Applications", Statistical Language Learning, Chapter 3, pp. 37-73 (The MIT... (Read Full Article)

    Comment on Article Mentions:   Information Processing Society of Japan   Eugene Charniak   MIT Press

  14. Apparatus and method for generating digest according to hierarchical structure of topic

    Explore Article PatFT » Page 1 of 1 (Oct 28 2003) Summarization

    ...ng the propriety of a series of words using useprobability estimated by training data is reported, (Eugene Charniak, "Hidden Markov Models and Two applications", in Statistical Language Learning, Chapter 3, pp.37 to... (Read Full Article)

    Comment on Article Mentions:   Institute of Electronics   Eugene Charniak   Hearst

  15. Summarization apparatus and method

    Explore Article PatFT » Page 1 of 1 (Mar 20 2001) Summarization

    ...P backward-A* N-best search algorithm. In Proceedings of COLING '94, pp. 201-207, 1994.Document 10: Eugene Charniak. Hidden markov models and two applications. In Statistical Language Learning, chapter 3, pp. 37-73.... (Read Full Article)

    Comment on Article Mentions:   Intel   Tanzania   Texas Instruments

1-14 of 14