Peer Evaluation activity
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IBM T. J. Watson Research Center
Learning to Predict Readability using Diverse Linguistic Features
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Author(s) : Rohit J Kate, Xiaoqiang Luo, Siddharth Patwardhan, Martin Franz, Radu Florian, Raymond J Mooney, Salim Roukos, Chris Welty
Subject : unspecified
Area : Other
Language : English
Year : 2010
|Affiliations :||IBM T. J. Watson Research Center|
Issue : August
Publisher : Coling 2010 Organizing Committee
Pages : 546-554
Url : http://www.aclweb.org/anthology/C10-1062
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Siddharth's Peer Evaluation activity
- 68OpinionFinder: A System for Subjectivity Analysis
- 62Identifying sources of opinions with conditional random fields and extraction patterns
- 52Learning to Predict Readability using Diverse Linguistic Features
- 6Identifying Sources of Opinions with Conditional Random Fields and
- 5Combining Global Relevance Information with Local Contextual Clues for Event-Oriented Information Extraction
- 4Using WordNet Based Context Vectors to Estimate the Semantic Relatedness of Concepts
- 4Maximizing Semantic Relatedness to Perform
- 4Feature Subsumption for Opinion Analysis
- 4Feature Subsumption for Opinion Analysis CLUESandCLASS
- 4Learning Domain-Specific Information Extraction Patterns from the Web
- 4Identifying Sources of Opinions with Conditional Random Fields and Extraction Patterns
- 3Identifying sources of opinions with conditional random fields and extraction patterns
- 3Using WordNet-based context vectors to estimate the semantic relatedness of concepts
- 1A unified model of phrasal and sentential evidence for information extraction
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