Jonathan Weese
Johns Hopkins University
17 Papers
211 Citations
Jonathan Weese is an academic researcher from Johns Hopkins University. The author has contributed to research in topics: Machine translation & Parsing. The author has an hindex of 11, co-authored 17 publications.
Chat about Author
Papers
•Proceedings Article
UMBC_EBIQUITY-CORE: Semantic Textual Similarity Systems
Lushan Han,Abhay L. Kashyap,Tim Finin,James Mayfield,Jonathan Weese +4 more
- 13 Jun 2013
TL;DR: Three semantic text similarity systems developed for the *SEM 2013 STS shared task used a simple term alignment algorithm augmented with penalty terms, and two used support vector regression models to combine larger sets of features.
•Proceedings Article
cdec: A Decoder, Alignment, and Learning Framework for Finite-State and Context-Free Translation Models
Chris Dyer,Adam Lopez,Juri Ganitkevitch,Jonathan Weese,Ferhan Ture,Phil Blunsom,Hendra Setiawan,Vladimir Eidelman,Philip Resnik +8 more
- 13 Jul 2010
TL;DR: For example, cdec as mentioned in this paper is an open source framework for decoding, aligning with, and training a number of statistical machine translation models, including word-based models, phrase-based model, and models based on synchronous context-free grammars.
•Proceedings Article
Joshua: An open source toolkit for parsing-based machine translation
Zhifei Li,Chris Callison-Burch,Chris Dyer,Juri Ganitkevitch,Sanjeev Khudanpur,Lane Schwartz,Wren N. G. Thornton,Jonathan Weese,Omar F. Zaidan +8 more
- 01 Mar 2009
TL;DR: Joshua implements all of the algorithms required for synchronous context free grammars (SCFGs): chart-parsing, n-gram language model integration, beam-and cube-pruning, and k-best extraction, and uses parallel and distributed computing techniques for scalability.
90
•Proceedings Article
Joshua 4.0: Packing, PRO, and Paraphrases
Juri Ganitkevitch,Yuan Cao,Jonathan Weese,Matt Post,Chris Callison-Burch +4 more
- 07 Jun 2012
TL;DR: The main contributions in this release are the introduction of a compact grammar representation based on packed tries, and the integration of the implementation of pairwise ranking optimization, J-PRO.
•Proceedings Article
Joshua 3.0: Syntax-based Machine Translation with the Thrax Grammar Extractor
Jonathan Weese,Juri Ganitkevitch,Chris Callison-Burch,Matt Post,Adam Lopez +4 more
- 30 Jul 2011
TL;DR: The main focus is describing Thrax, a flexible, open source synchronous context-free grammar extractor that is built on Apache Hadoop for efficient distributed performance and can easily be extended with support for new grammars, feature functions, and output formats.