Larry Smith
National Institutes of Health
7 Papers
10 Citations
Larry Smith is an academic researcher from National Institutes of Health. The author has contributed to research in topics: Sentence & Support vector machine. The author has an hindex of 4, co-authored 7 publications.
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Papers
Overview of BioCreative II gene mention recognition
Larry Smith,Lorraine K. Tanabe,Rie Johnson nee Ando,Cheng-Ju Kuo,I-Fang Chung,Chun-Nan Hsu,Yu-Shi Lin,Roman Klinger,Christoph M. Friedrich,Kuzman Ganchev,Manabu Torii,Hongfang Liu,Barry Haddow,Craig A. Struble,Richard J. Povinelli,Andreas Vlachos,William A. Baumgartner,Lawrence Hunter,Bob Carpenter,Richard Tzong-Han Tsai,Richard Tzong-Han Tsai,Hong-Jie Dai,Hong-Jie Dai,Feng Liu,Yifei Chen,Chengjie Sun,Sophia Katrenko,Pieter Adriaans,Christian Blaschke,Rafael Torres,Mariana Neves,Preslav Nakov,Preslav Nakov,Anna Divoli,Manuel Maña-López,Jacinto Mata,W. John Wilbur +36 more
TL;DR: It is demonstrated that, by combining the results from all submissions, an F score of 0.9066 is feasible, and furthermore that the best result makes use of the lowest scoring submissions.
Evaluation of text-mining systems for biology: overview of the Second BioCreative community challenge
Martin Krallinger,Alexander A. Morgan,Larry Smith,Florian Leitner,Lorraine K. Tanabe,W. John Wilbur,Lynette Hirschman,Alfonso Valencia +7 more
TL;DR: A common characteristic observed in all three tasks was that the combination of system outputs could yield better results than any single system, including the development of the first text-mining meta-server.
The value of parsing as feature generation for gene mention recognition
Larry Smith,W. John Wilbur +1 more
TL;DR: Using the GENETAG corpus as a gold standard, machine learning was performed to recognize from its context when a base noun phrase contained a gene name.
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•Proceedings Article
PROBE: Periodic Random Orbiter Algorithm for Machine Learning.
Larry Smith,Won Kim,W. John Wilbur +2 more
- 01 Jan 2012
TL;DR: PROBE is a simple and easily programmed algorithm, with a well-defined, parametrized stopping criterion, that is not limited to SVM, but can be applied to other convex loss functions, such as the Hu-ber and Maximum Entropy models.
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Exploratory Genomic Data Analysis
Larry Smith
- 01 Jan 2005
TL;DR: This chapter focuses on one type of data, gene expression profiling by microarray technology, and one method of analysis, cluster analysis for discovering and sorting mixed populations.
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