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Learning Categories and their Instances by Contextual Features.

, and . LREC, page 1235-1239. European Language Resources Association (ELRA), (2012)

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Labeling Queries for a People Search Engine., , , and . NLDB, volume 7337 of Lecture Notes in Computer Science, page 47-57. Springer, (2012)ExB Themis: Extensive Feature Extraction from Word Alignments for Semantic Textual Similarity., , and . SemEval@NAACL-HLT, page 264-268. The Association for Computer Linguistics, (2015)Textual Characteristics for Language Engineering., , and . LREC, page 515-519. European Language Resources Association (ELRA), (2012)Learning Categories and their Instances by Contextual Features., and . LREC, page 1235-1239. European Language Resources Association (ELRA), (2012)Modeling and Representing Negation in Data-driven Machine Learning-based Sentiment Analysis.. ESSEM@AI*IA, volume 1096 of CEUR Workshop Proceedings, page 22-33. CEUR-WS.org, (2013)Improving Sentence-level Subjectivity Classification through Readability Measurement.. NODALIDA, page 168-174. Northern European Association for Language Technology (NEALT) / Tartu University Library (Estonia) / ACL, (2011)SentiWS - A Publicly Available German-language Resource for Sentiment Analysis., , and . LREC, European Language Resources Association, (2010)Domain Adaptation Using Domain Similarity- and Domain Complexity-Based Instance Selection for Cross-Domain Sentiment Analysis.. ICDM Workshops, page 717-723. IEEE Computer Society, (2012)ASVUniOfLeipzig: Sentiment Analysis in Twitter using Data-driven Machine Learning Techniques.. SemEval@NAACL-HLT, page 450-454. The Association for Computer Linguistics, (2013)