Daniel Marcu focuses on Artificial intelligence, Natural language processing, Natural language, Machine translation and Linguistics. His research combines Machine learning and Artificial intelligence. His Natural language processing study incorporates themes from Rhetorical Structure Theory and Discourse relation.
His Machine translation research includes themes of Speech recognition and Translation. In Linguistics, he works on issues like Parsing, which are connected to Rhetorical question and Natural language generation. His Phrase research is multidisciplinary, incorporating elements of Machine translation software usability, Determiner phrase and Dependency grammar.
The scientist’s investigation covers issues in Artificial intelligence, Natural language processing, Machine translation, Speech recognition and Linguistics. His work in Rule-based machine translation, Natural language, Translation, Word and Parsing is related to Artificial intelligence. His Natural language research integrates issues from Binary classification and Machine learning, Structured prediction.
His biological study spans a wide range of topics, including Decoding methods, Soft-decision decoder and Set. His Parsing research includes elements of Natural language generation and Rhetorical question. His is doing research in Phrase, Automatic summarization, Example-based machine translation, Sentence and Syntax, both of which are found in Natural language processing.
Artificial intelligence, Natural language processing, Translation, Word and Machine translation are his primary areas of study. His Artificial intelligence research incorporates elements of Machine learning and Ambiguity. His research on Natural language processing frequently links to adjacent areas such as Information retrieval.
His Language translation and Translation system study in the realm of Translation interacts with subjects such as Trust score. His Word study integrates concerns from other disciplines, such as Speech recognition, Set and Pattern recognition. In his research on the topic of Machine translation, NIST, Domain, Syntax, Language model and Programming language is strongly related with Representation.
Daniel Marcu mostly deals with Artificial intelligence, Natural language processing, Translation, Natural language and Rule-based machine translation. As part of the same scientific family, Daniel Marcu usually focuses on Artificial intelligence, concentrating on Machine learning and intersecting with Machine translation. His Natural language processing research incorporates themes from Robot and Human–computer interaction.
His work on Computer-assisted translation as part of general Translation study is frequently linked to Metric, bridging the gap between disciplines. His Natural language research is multidisciplinary, incorporating perspectives in Binary classification, Feature, Structured prediction and Class. His Rule-based machine translation study combines topics from a wide range of disciplines, such as Sentence, Semantics, Semantics and Ambiguity.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
Statistical phrase-based translation
Philipp Koehn;Franz Josef Och;Daniel Marcu.
north american chapter of the association for computational linguistics (2003)
Domain adaptation for statistical classifiers
Hal Daumé;Daniel Marcu.
Journal of Artificial Intelligence Research (2006)
The Theory and Practice of Discourse Parsing and Summarization
The Rhetorical Parsing of Unrestricted Natural Language Texts
meeting of the association for computational linguistics (1997)
A Phrase-Based,Joint Probability Model for Statistical Machine Translation
Daniel Marcu;Daniel Wong.
empirical methods in natural language processing (2002)
What's in a Translation Rule
Michel Galley;Mark Hopkins;Kevin Knight;Daniel Marcu.
north american chapter of the association for computational linguistics (2004)
Building a discourse-tagged corpus in the framework of Rhetorical Structure Theory
Lynn Carlson;Daniel Marcu;Mary Ellen Okurowski.
annual meeting of the special interest group on discourse and dialogue (2001)
Summarization beyond sentence extraction: a probabilistic approach to sentence compression
Kevin Knight;Daniel Marcu.
Artificial Intelligence (2002)
Scalable Inference and Training of Context-Rich Syntactic Translation Models
Michel Galley;Jonathan Graehl;Kevin Knight;Daniel Marcu.
meeting of the association for computational linguistics (2006)
Statistics-Based Summarization - Step One: Sentence Compression
Kevin Knight;Daniel Marcu.
national conference on artificial intelligence (2000)
Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking h-index is inferred from publications deemed to belong to the considered discipline.
If you think any of the details on this page are incorrect, let us know.
We appreciate your kind effort to assist us to improve this page, it would be helpful providing us with as much detail as possible in the text box below: