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Lecture Notes in Computer Science
This paper considers the task of sentiment classification of subjective text across many domains, in particular on scenarios where no in-domain data is available. Motivated by the more general applicability of such methods, we propose an extensible approach to sentiment classification that leverages sentiment lexicons and out-of-domain data to build a case-based system where solutions to past cases are reused to predict the sentiment of new documents from an unknown domain. In our approach thedoi:10.1007/978-3-642-32986-9_22 fatcat:625he6lmajcgbndvwifjld44zm