Ralph Weischedel mainly investigates Artificial intelligence, Natural language processing, Annotation, Structure and Information retrieval. His Artificial intelligence research includes elements of Algorithm, Machine learning and Speech recognition. The various areas that Ralph Weischedel examines in his Speech recognition study include Translation, Postediting, Hybrid machine translation and Interactive machine translation.
His research ties Probabilistic logic and Natural language processing together. His research integrates issues of Semantic analysis, Semantic representation, Coreference and Semantic network in his study of Annotation. His Information retrieval course of study focuses on Language model and Question answering and Human–computer information retrieval.
Ralph Weischedel focuses on Artificial intelligence, Natural language processing, Information retrieval, Natural language and Language model. His Artificial intelligence research integrates issues from Machine learning and Speech recognition. The concepts of his Natural language processing study are interwoven with issues in Annotation and Probabilistic logic.
His Information retrieval study combines topics from a wide range of disciplines, such as Set and Simple Features. His work focuses on many connections between Natural language and other disciplines, such as Semantics, that overlap with his field of interest in Text processing. His studies in Language model integrate themes in fields like Sentence, Computational linguistics and Computation.
Ralph Weischedel mainly focuses on Artificial intelligence, Natural language processing, Language model, Human–computer interaction and Quality. His studies deal with areas such as Decision problem and Relation as well as Artificial intelligence. His studies in Natural language processing integrate themes in fields like Annotation and Rule-based system.
His studies deal with areas such as Cohesion, Narrative text, Sentence and Natural language understanding as well as Language model. His biological study spans a wide range of topics, including Metric and Natural language. As a member of one scientific family, Ralph Weischedel mostly works in the field of Quality, focusing on Open domain and, on occasion, Machine learning.
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A Study of Translation Edit Rate with Targeted Human Annotation
Matthew G. Snover;Bonnie J. Dorr;Richard M. Schwartz;Linnea Micciulla.
conference of the association for machine translation in the americas (2006)
The Automatic Content Extraction (ACE) Program Tasks, Data, and Evaluation
George R. Doddington;Alexis Mitchell;Mark A. Przybocki;Lance A. Ramshaw.
language resources and evaluation (2004)
An Algorithm that Learns What‘s in a Name
Daniel M. Bikel;Richard Schwartz;Ralph M. Weischedel.
Machine Learning (1999)
OntoNotes: The 90% Solution
Eduard Hovy;Mitchell Marcus;Martha Palmer;Lance Ramshaw.
north american chapter of the association for computational linguistics (2006)
Nymble: a High-Performance Learning Name-finder
Daniel M. Bikel;Scott Miller;Richard Schwartz;Ralph Weischedel.
conference on applied natural language processing (1997)
PERFORMANCE MEASURES FOR INFORMATION EXTRACTION
John Makhoul;Francis Kubala;Richard Schwartz;Ralph Weischedel.
Coping with ambiguity and unknown words through probabilistic models
Ralph Weischedel;Richard Schwartz;Jeff Palmucci;Marie Meteer.
Computational Linguistics (1993)
CoNLL-2011 Shared Task: Modeling Unrestricted Coreference in OntoNotes
Sameer Pradhan;Lance Ramshaw;Mitchell Marcus;Martha Palmer.
conference on computational natural language learning (2011)
A New String-to-Dependency Machine Translation Algorithm with a Target Dependency Language Model
Libin Shen;Jinxi Xu;Ralph Weischedel.
meeting of the association for computational linguistics (2008)
A novel use of statistical parsing to extract information from text
Scott Miller;Heidi Fox;Lance Ramshaw;Ralph Weischedel.
north american chapter of the association for computational linguistics (2000)
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