@inproceedings{bethard-etal-2014-cleartk,
title = "{C}lear{TK} 2.0: Design Patterns for Machine Learning in {UIMA}",
author = "Bethard, Steven and
Ogren, Philip and
Becker, Lee",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/218_Paper.pdf",
pages = "3289--3293",
abstract = "ClearTK adds machine learning functionality to the UIMA framework, providing wrappers to popular machine learning libraries, a rich feature extraction library that works across different classifiers, and utilities for applying and evaluating machine learning models. Since its inception in 2008, ClearTK has evolved in response to feedback from developers and the community. This evolution has followed a number of important design principles including: conceptually simple annotator interfaces, readable pipeline descriptions, minimal collection readers, type system agnostic code, modules organized for ease of import, and assisting user comprehension of the complex UIMA framework.",
}
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%0 Conference Proceedings
%T ClearTK 2.0: Design Patterns for Machine Learning in UIMA
%A Bethard, Steven
%A Ogren, Philip
%A Becker, Lee
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F bethard-etal-2014-cleartk
%X ClearTK adds machine learning functionality to the UIMA framework, providing wrappers to popular machine learning libraries, a rich feature extraction library that works across different classifiers, and utilities for applying and evaluating machine learning models. Since its inception in 2008, ClearTK has evolved in response to feedback from developers and the community. This evolution has followed a number of important design principles including: conceptually simple annotator interfaces, readable pipeline descriptions, minimal collection readers, type system agnostic code, modules organized for ease of import, and assisting user comprehension of the complex UIMA framework.
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/218_Paper.pdf
%P 3289-3293
Markdown (Informal)
[ClearTK 2.0: Design Patterns for Machine Learning in UIMA](http://www.lrec-conf.org/proceedings/lrec2014/pdf/218_Paper.pdf) (Bethard et al., LREC 2014)
ACL
- Steven Bethard, Philip Ogren, and Lee Becker. 2014. ClearTK 2.0: Design Patterns for Machine Learning in UIMA. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 3289–3293, Reykjavik, Iceland. European Language Resources Association (ELRA).