U-Compare
Yoshinobu Kano,William A. Baumgartner,Luke McCrohon,Sophia Ananiadou,K. Bretonnel Cohen,Lawrence Hunter,Jun'ichi Tsujii +6 more
TL;DR: U-Compare is a joint project, providing the world's largest, and still growing, collection of UIMA-compatible resources, providing both a concrete framework for out-of-the-box text mining and a sophisticated evaluation platform allowing users to run specific tools on any target text.
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Abstract: Summary: Due to the increasing number of text mining resources (tools and corpora) available to biologists, interoperability issues between these resources are becoming significant obstacles to using them effectively. UIMA, the Unstructured Information Management Architecture, is an open framework designed to aid in the construction of more interoperable tools. U-Compare is built on top of the UIMA framework, and provides both a concrete framework for out-of-the-box text mining and a sophisticated evaluation platform allowing users to run specific tools on any target text, generating both detailed statistics and instance-based visualizations of outputs. U-Compare is a joint project, providing the world's largest, and still growing, collection of UIMA-compatible resources. These resources, originally developed by different groups for a variety of domains, include many famous tools and corpora. U-Compare can be launched straight from the web, without needing to be manually installed. All U-Compare components are provided ready-to-use and can be combined easily via a drag-and-drop interface without any programming. External UIMA components can also simply be mixed with U-Compare components, without distinguishing between locally and remotely deployed resources.
Availability: http://u-compare.org/
Contact: kano@is.s.u-tokyo.ac.jp
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Guergana Savova,James J. Masanz,Philip V. Ogren,Jiaping Zheng,Sunghwan Sohn,Karin C Kipper-Schuler,Christopher G. Chute +6 more
TL;DR: The cTAKES annotations are the foundation for methods and modules for higher-level semantic processing of clinical free-text, and its components, specifically trained for the clinical domain, create rich linguistic and semantic annotations.
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References
Text mining and its potential applications in systems biology
TL;DR: By adding meaning to text, text mining techniques produce a more structured analysis of textual knowledge than simple word searches, and can provide powerful tools for the production and analysis of systems biology models.
372
An open-source framework for large-scale, flexible evaluation of biomedical text mining systems.
TL;DR: A publicly available framework that facilitates thorough, structured, and large-scale evaluations of text mining technologies and demonstrates the potential for novel discovery resulting from the structured evaluation of biomedical language processing systems.
Filling the gaps between tools and users: a tool comparator, using protein-protein interaction as an example.
Yoshinobu Kano,Ngan Luu-Thuy Nguyen,Rune Sætre,Kazuhiro Yoshida,Yusuke Miyao,Yoshimasa Tsuruoka,Yuichiroh Matsubayashi,Sophia Ananiadou,Jun'ichi Tsujii,Jun'ichi Tsujii +9 more
- 01 Dec 2007
TL;DR: An environment that was developed based on UIMA is described and its feasibility is shown through the experience in developing a protein-protein interaction (PPI) extraction system.
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