Abstract
Along with the growth of Internet, Web is glutted with more and more illegal and harmful information, such as pornography, violence, horror information. For a long time, researchers pay little attention to horror information relative to pornography. Horror information as well as pornography harms youngsters’ health seriously. In order to recognize horror information, in this paper, we propose a horror text recognition algorithm based on two classifiers, in which one is text title classifier, and the other is text content classifier based on generalized expectation (GE) criteria. A generalized expectation criterion is a term in a parameter estimation objective function that assigns scores which can express preferences to values of a model expectation. In this paper, this parameter estimation objective function is used for measuring the correlation between features and sentiment labels.
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Liu, G., Li, B., Hu, W., Yang, J. (2013). Horror Text Recognition Based on Generalized Expectation Criteria. In: Sun, C., Fang, F., Zhou, ZH., Yang, W., Liu, ZY. (eds) Intelligence Science and Big Data Engineering. IScIDE 2013. Lecture Notes in Computer Science, vol 8261. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-42057-3_18
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DOI: https://doi.org/10.1007/978-3-642-42057-3_18
Publisher Name: Springer, Berlin, Heidelberg
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