TY - GEN
T1 - ClearTK 2.0
T2 - 9th International Conference on Language Resources and Evaluation, LREC 2014
AU - Bethard, Steven
AU - Ogren, Philip
AU - Becker, Lee
N1 - Funding Information:
This research was supported in part by the Strategic Health IT Advanced Research Projects (SHARP) Program (90TR002) from the Office of the National Coordinator for Health Information Technology, and by Grant Number R01LM010090 from the National Library Of Medicine. The content is solely the responsibility of the authors and does not necessarily represent the official views of the Office of the National Coordinator for Health Information Technology, the National Library Of Medicine or the National Institutes of Health.
PY - 2014
Y1 - 2014
N2 - 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.
AB - 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.
KW - Machine learning
KW - NLP frameworks
KW - UIMA
UR - http://www.scopus.com/inward/record.url?scp=85035782630&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85035782630&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:85035782630
T3 - Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014
SP - 3289
EP - 3293
BT - Proceedings of the 9th International Conference on Language Resources and Evaluation, LREC 2014
A2 - Calzolari, Nicoletta
A2 - Choukri, Khalid
A2 - Goggi, Sara
A2 - Declerck, Thierry
A2 - Mariani, Joseph
A2 - Maegaard, Bente
A2 - Moreno, Asuncion
A2 - Odijk, Jan
A2 - Mazo, Helene
A2 - Piperidis, Stelios
A2 - Loftsson, Hrafn
PB - European Language Resources Association (ELRA)
Y2 - 26 May 2014 through 31 May 2014
ER -