Abstract
Opinion mining is the process of analyzing views, attitude or opinions of a writer or a speaker. Research in this particular area involves the detection of opinions from the text of any language. Vast amount of work has been done for the English language. In spite of lack of resources for Indian languages, work has been done for Telugu, Bengali and Hindi language. In this paper, we proposed a hybrid research approach for the emotion/opinion mining of the Punjabi text. Hybrid technique is the combination of Naïve Bayes and N-grams. As the part of presented research, we have extracted the features of N-grams model which are used to train Naïve Bayes. The trained model is then validated using the testing data. Results obtained are also compared with already existing approaches and the accuracy of the results shows the better efficacy of the proposed method.
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Kaur, A., Gupta, V. (2014). N-gram Based Approach for Opinion Mining of Punjabi Text. In: Murty, M.N., He, X., Chillarige, R.R., Weng, P. (eds) Multi-disciplinary Trends in Artificial Intelligence. MIWAI 2014. Lecture Notes in Computer Science(), vol 8875. Springer, Cham. https://doi.org/10.1007/978-3-319-13365-2_8
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DOI: https://doi.org/10.1007/978-3-319-13365-2_8
Publisher Name: Springer, Cham
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