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You searched for +publisher:"University of Southern California" +contributor:("Chiang, David"). Showing records 1 – 5 of 5 total matches.

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University of Southern California

1. Tratz, Stephen Charles. Semantically-enriched parsing for natural language understanding.

Degree: PhD, Computer Science, 2011, University of Southern California

 This thesis details three contributions to the advancement of semantic-enriched parsing for English sentences: inventories of semantic relations covering three semantically ambiguous linguistic phenomena, large… (more)

Subjects/Keywords: computational linguistics; parsing; semantics; noun compounds; prepositions; possessives; easy-first

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APA (6th Edition):

Tratz, S. C. (2011). Semantically-enriched parsing for natural language understanding. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/176191/rec/5778

Chicago Manual of Style (16th Edition):

Tratz, Stephen Charles. “Semantically-enriched parsing for natural language understanding.” 2011. Doctoral Dissertation, University of Southern California. Accessed November 19, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/176191/rec/5778.

MLA Handbook (7th Edition):

Tratz, Stephen Charles. “Semantically-enriched parsing for natural language understanding.” 2011. Web. 19 Nov 2019.

Vancouver:

Tratz SC. Semantically-enriched parsing for natural language understanding. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Nov 19]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/176191/rec/5778.

Council of Science Editors:

Tratz SC. Semantically-enriched parsing for natural language understanding. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/176191/rec/5778


University of Southern California

2. Ravi, Sujith. Deciphering natural language.

Degree: PhD, Computer Science, 2011, University of Southern California

 Most state-of-the-art techniques used in natural language processing (NLP) are supervised and require labeled training data. For example, statistical language translation requires huge amounts of… (more)

Subjects/Keywords: natural language processing; machine learning; computational decipherment; artificial intelligence; statistics

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APA (6th Edition):

Ravi, S. (2011). Deciphering natural language. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/448537/rec/1788

Chicago Manual of Style (16th Edition):

Ravi, Sujith. “Deciphering natural language.” 2011. Doctoral Dissertation, University of Southern California. Accessed November 19, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/448537/rec/1788.

MLA Handbook (7th Edition):

Ravi, Sujith. “Deciphering natural language.” 2011. Web. 19 Nov 2019.

Vancouver:

Ravi S. Deciphering natural language. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Nov 19]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/448537/rec/1788.

Council of Science Editors:

Ravi S. Deciphering natural language. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/448537/rec/1788


University of Southern California

3. DeNeefe, Steve. Tree-adjoining machine translation.

Degree: PhD, Computer Science, 2011, University of Southern California

 Machine Translation (MT) is the task of translating a document from a source language (e.g., Chinese) into a target language (e.g., English) via computer. State-of-the-art… (more)

Subjects/Keywords: machine translation; statistical machine translation; tree-adjoining grammar; formal grammar; translation models; computational linguistics; syntax-based machine translation

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APA (6th Edition):

DeNeefe, S. (2011). Tree-adjoining machine translation. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/667127/rec/7600

Chicago Manual of Style (16th Edition):

DeNeefe, Steve. “Tree-adjoining machine translation.” 2011. Doctoral Dissertation, University of Southern California. Accessed November 19, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/667127/rec/7600.

MLA Handbook (7th Edition):

DeNeefe, Steve. “Tree-adjoining machine translation.” 2011. Web. 19 Nov 2019.

Vancouver:

DeNeefe S. Tree-adjoining machine translation. [Internet] [Doctoral dissertation]. University of Southern California; 2011. [cited 2019 Nov 19]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/667127/rec/7600.

Council of Science Editors:

DeNeefe S. Tree-adjoining machine translation. [Doctoral Dissertation]. University of Southern California; 2011. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/667127/rec/7600


University of Southern California

4. Hovy, Dirk. Learning semantic types and relations from text.

Degree: PhD, Computer Science, 2013, University of Southern California

 NLP applications such as Question Answering (QA), Information Extraction (IE), or Machine Translation (MT) are incorporating increasing amounts of semantic information. A fundamental building block… (more)

Subjects/Keywords: NLP; computational linguistics; information extraction; relation extraction; unsupervised learning

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APA (6th Edition):

Hovy, D. (2013). Learning semantic types and relations from text. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/300459/rec/3785

Chicago Manual of Style (16th Edition):

Hovy, Dirk. “Learning semantic types and relations from text.” 2013. Doctoral Dissertation, University of Southern California. Accessed November 19, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/300459/rec/3785.

MLA Handbook (7th Edition):

Hovy, Dirk. “Learning semantic types and relations from text.” 2013. Web. 19 Nov 2019.

Vancouver:

Hovy D. Learning semantic types and relations from text. [Internet] [Doctoral dissertation]. University of Southern California; 2013. [cited 2019 Nov 19]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/300459/rec/3785.

Council of Science Editors:

Hovy D. Learning semantic types and relations from text. [Doctoral Dissertation]. University of Southern California; 2013. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll3/id/300459/rec/3785


University of Southern California

5. May, Jonathan David Louis. Weighted tree automata and transducers for syntactic natural language processing.

Degree: PhD, Computer Science, 2010, University of Southern California

 Weighted finite-state string transducer cascades are a powerful formalism for models of solutions to many natural language processing problems such as speech recognition, transliteration, and… (more)

Subjects/Keywords: computational linguistics; natural language processing; machine translation; parsing; tree automata; tree transducers; context-free grammars; finite state machines; machine learning

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

May, J. D. L. (2010). Weighted tree automata and transducers for syntactic natural language processing. (Doctoral Dissertation). University of Southern California. Retrieved from http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/344748/rec/7874

Chicago Manual of Style (16th Edition):

May, Jonathan David Louis. “Weighted tree automata and transducers for syntactic natural language processing.” 2010. Doctoral Dissertation, University of Southern California. Accessed November 19, 2019. http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/344748/rec/7874.

MLA Handbook (7th Edition):

May, Jonathan David Louis. “Weighted tree automata and transducers for syntactic natural language processing.” 2010. Web. 19 Nov 2019.

Vancouver:

May JDL. Weighted tree automata and transducers for syntactic natural language processing. [Internet] [Doctoral dissertation]. University of Southern California; 2010. [cited 2019 Nov 19]. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/344748/rec/7874.

Council of Science Editors:

May JDL. Weighted tree automata and transducers for syntactic natural language processing. [Doctoral Dissertation]. University of Southern California; 2010. Available from: http://digitallibrary.usc.edu/cdm/compoundobject/collection/p15799coll127/id/344748/rec/7874

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