MỘT SỐ PHƯƠNG PHÁP MÁY HỌC ỨNG DỤNG TRONG PHÂN LOẠI Ý KIẾN CỦA NGƯỜI DÙNG TRÊN CÁC TRANG MẠNG
Abstract
Ngày nay, trước khi đưa ra một quyết định nào đó, chúng ta thường tham khảo ý kiến của những người dùng trên các trang mạng vì những ý kiến này thường là nhân tố chi phối hành vi của con người. Ý kiến (hay quan điểm) thường được diễn đạt theo ba thái cực: lạc quan (positive), bi quan (negative) và trung lập (neutral). Trong bài viết này, chúng tôi khảo sát một số kỹ thuật máy học và đưa ra nhận định về khả năng ứng dụng của các kỹ thuật này trong phân loại tự động ý kiến của người dùng trên các trang mạng.References
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[3] Chen, C. C., & Tseng, Y. D. (2011). Quality evaluation of product reviews using an information quality framework. Decision Support Systems, 50(4), 755-768.
[4] Hu, Y., & Li, W. (2011). Document sentiment classification by exploring description model of topical terms. Computer Speech & Language, 25(2), 386-403.
[5] Joachims, T. (1996). A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization (No. CMU-CS-96-118). CARNEGIE-MELLON UNIV PITTSBURGH PA DEPT OF COMPUTER SCIENCE.
[6] Kaufmann, M. (2012, December). JMaxAlign: A Maximum Entropy Parallel Sentence Alignment Tool. In COLING (Demos) (pp. 277-288).
[7] Li, Y. H., & Jain, A. K. (1998). Classification of text documents. The Computer Journal, 41(8), 537-546.
[8] Li, Y. M., & Li, T. Y. (2013). Deriving market intelligence from microblogs. Decision Support Systems, 55(1), 206-217.
[9] Liu, B. (2012). Sentiment analysis and opinion mining. Synthesis Lectures on Human Language Technologies, 5(1), 1-167.
[10] Ma, B. L. W. H. Y. (1998, August). Integrating classification and association rule mining. In Proceedings of the fourth international conference on knowledge discovery and data mining.
[11] Medhat, W., Hassan, A., & Korashy, H. (2014). Sentiment analysis algorithms and applications: A survey. Ain Shams Engineering Journal, 5(4), 1093-1113.
[12] Medhat, W., Yousef, A. H., & Mohamed, H. K. (2014). Combined algorithm for data mining using association rules. arXiv preprint arXiv:1410.1343.
[13] Moraes, R., Valiati, J. F., & Neto, W. P. G. (2013). Document-level sentiment classification: An empirical comparison between SVM and ANN. Expert Systems with Applications, 40(2), 621-633.
[14] Ortigosa-Hernández, J., Rodríguez, J. D., Alzate, L., Lucania, M., Inza, I., & Lozano, J. A. (2012). Approaching Sentiment Analysis by using semi-supervised learning of multi dimensional classifiers. Neurocomputing, 92, 98-115.
[15] Pang, B., & Lee, L. (2008). Opinion mining and sentiment analysis. Foundations and trends in information retrieval, 2(1-2), 1-135.
[16] Quinlan, J. R. (1986). Induction of decision trees. Machine learning, 1(1), 81-106.
[17] Van De Camp, M., & Van Den Bosch, A. (2012). The socialist network. Decision Support Systems, 53(4), 761-769.
[18] Yan-Yan, Z., Bing, Q., & Ting, L. (2010). Integrating intra-and inter-document evidences for improving sentence sentiment classification. Acta Automatica Sinica, 36(10), 1417- 1425.
[19] Diana Maynard, Adam Funk. Proceedings of the 8th international conference on the semantic Web, Automatic detection of political opinions in tweets, ESWC’11; 2011.p.88-89
[20] Thomas, D. Nielsen & Finn V. Jensen (2007). Bayesian Networks and Decision Graph,
[21] Manning, D. Christopher & Schutze, Hinrich (1999). Foundations of Statistical Natural Language Processing. The MIT Press.
[22] Kang Hanhoon, Yoo Seong Joon, Han Dongil. Senti-lexicon and improved Naıve Bayes algorithms for sentiment analysis of restaurant reviews. Expert Syst Appl 2012;39:6000– 10.
Published
2015-12-18
How to Cite
HUY, Bùi Xuân; TÂM, Phạm Thị Thanh; PHỤNG, Thái Kim.
MỘT SỐ PHƯƠNG PHÁP MÁY HỌC ỨNG DỤNG TRONG PHÂN LOẠI Ý KIẾN CỦA NGƯỜI DÙNG TRÊN CÁC TRANG MẠNG.
JBIS, [S.l.], dec. 2015.
Available at: <https://jbis.ueh.edu.vn/index.php/TSTHQL/article/view/79>. Date accessed: 19 may 2024.
Issue
Section
Bài viết
Keywords
khai thác ý kiến; phân loại ý kiến; phân loại cảm xúc
