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Learning with Compositional Semantics as Structural Inference for Subsentential Sentiment Analysis Yejin Choi and Claire Cardie Department of Computer Science Cornell University Ithaca, NY 14853
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Document Date: 2014-10-31 15:21:37


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Heuristic / Learning / /

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Yale University Press / /

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dot product / online algorithms / propagation algorithm / /

Organization

American Medical Informatics Association / SC SC / National Science Foundation / Cornell / Subsentential Sentiment Analysis Yejin Choi and Claire Cardie Department of Computer Science Cornell University Ithaca / Claire Cardie Department of Computer Science Cornell University Ithaca / Yale University / Association for Computational Linguistics / /

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Rada Mihalcea / David R. Dowty / Cleo Condoravdi / C OMPO PR / Karo Moilanen / Richard Montague / Soo-Min Kim / Xiaodan Zhu / Kerry Hannan / Carlo Strapparava / Robert E. Wall / Jianhua Li / Graeme Hirst / Jeff Reynar / P LEASUR / V / Mike Wells / Janyce Wiebe / Claire Cardie / Eduard Hovy / Paul Hoffmann / Diana Inkpen / Alistair Kennedy / Mitsuru Ishizuka / Theresa Wilson / Percy Liang / Helmut Prendinger / Mostafa Shaikh / C OMPO MC / Fabrizio Sebastiani / Lillian Lee / Yun Niu / Bing Liu / Tyler Neylon / Ryan McDonald / Eric Breck / Stanley Peters / Rowan Nairn / George A. Miller / Livia Polanyi / Lauri Karttunen / Minqing Hu / Dan Klein / Montague Semantics / Hal Daum / Stephen Pulman / Steven Abney / Annie Zaenen / Andrea Esuli / /

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South Carolina / /

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Computational Linguistics / Machine Learning / Communications of the ACM / /

Technology

Natural Language Processing / online SVM algorithm / propagation algorithm / Java / Ultraconservative online algorithms / Data Mining / machine learning / html / /

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