2014 - ACM Fellow For contributions to natural-language processing, and to open-access systems and policy.
2004 - Fellow of the Association for the Advancement of Artificial Intelligence (AAAI) For significant contributions to the foundations of computational linguistics, to graphical and spokenlanguage interfaces, and to open scientific publishing.
Stuart M. Shieber mainly investigates Artificial intelligence, Natural language processing, Rule-based machine translation, Theoretical computer science and Algorithm. His Artificial intelligence research is multidisciplinary, incorporating elements of Machine learning and Control. His biological study spans a wide range of topics, including Programming language, Linguistics, Quantifier and Phrase structure rules.
His work deals with themes such as Treebank, Parsing, Semantic interpretation, Logical form and Syntax, which intersect with Rule-based machine translation. His Theoretical computer science research incorporates themes from Graph drawing, Computational resource and Technical drawing tools. His Algorithm research includes elements of Sentence, Feature, String and Heuristic.
His primary scientific interests are in Artificial intelligence, Natural language processing, Rule-based machine translation, Parsing and Programming language. His research in Artificial intelligence is mostly concerned with Natural language. His research on Natural language processing often connects related topics like Word.
Stuart M. Shieber usually deals with Rule-based machine translation and limits it to topics linked to Theoretical computer science and Algorithm. His research in Parsing intersects with topics in Rewriting, Probabilistic logic and Grammar. The study incorporates disciplines such as Generative grammar and Formalism in addition to Programming language.
His scientific interests lie mostly in Artificial intelligence, Natural language processing, Machine learning, Sentence and Word. He combines subjects such as Tree and Simple with his study of Artificial intelligence. His research investigates the link between Natural language processing and topics such as Control that cross with problems in Uninterpretable.
The concepts of his Sentence study are interwoven with issues in Empirical research, Grammar, Block and Reading. The various areas that Stuart M. Shieber examines in his Word study include Brainstorming, Information sharing and Speech processing. His Training set study combines topics from a wide range of disciplines, such as Variety, Linguistics, Readability and Deep learning.
His primary areas of study are Artificial intelligence, Machine learning, Natural language processing, Natural language inference and Sentence. His studies in Artificial intelligence integrate themes in fields like Spurious relationship and Control. Stuart M. Shieber performs multidisciplinary study in Natural language processing and Sequence in his work.
Stuart M. Shieber has included themes like Contrast, Baseline, Premise and Probabilistic method in his Natural language inference study. His Sentence research is multidisciplinary, incorporating perspectives in Identification, Scientific writing, Word, Binary number and Character. His Coreference research is multidisciplinary, relying on both Recurrent neural network and State.
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An introduction to unification-based approaches to grammar
Stuart M. Shieber.
Evidence Against the Context-Freeness of Natural Language
Stuart M. Shieber.
Linguistics and Philosophy (1985)
Ellipsis and higher-order unification
Mary Dalrymple;Stuart M. Shieber;Fernando C. N. Pereira.
Linguistics and Philosophy (1991)
Design galleries: a general approach to setting parameters for computer graphics and animation
J. Marks;B. Andalman;P. A. Beardsley;W. Freeman.
international conference on computer graphics and interactive techniques (1997)
Prolog and Natural-Language Analysis
Fernando C. N. Pereira;Stuart M. Shieber.
An empirical study of algorithms for point-feature label placement
Jon Christensen;Joe Marks;Stuart Shieber.
ACM Transactions on Graphics (1995)
Principles and implementation of deductive parsing
Stuart M. Shieber;Yves Schabes;Fernando C.N. Pereira.
Journal of Logic Programming (1995)
Synchronous tree-adjoining grammars
Stuart M. Shieber;Yves Schabes.
international conference on computational linguistics (1990)
Challenges in Data-to-Document Generation
Sam Joshua Wiseman;Stuart Merrill Shieber;Alexander Sasha Matthew Rush.
empirical methods in natural language processing (2017)
Command parsing and rewrite system
Stuart M. Shieber;John Armstrong;Rafael Jose Baptista;Bryan A. Bentz.
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