Open Access
| Issue |
MATEC Web of Conferences
Volume 58, 2016
The 3rd Bali International Seminar on Science & Technology (BISSTECH 2015)
|
|
|---|---|---|
| Article Number | 03003 | |
| Number of page(s) | 7 | |
| Section | Information Technology and Information Systems | |
| DOI | https://doi.org/10.1051/matecconf/20165803003 | |
| Published online | 23 May 2016 | |
- Coenen, F., Goulbourne, G. & Leng, P., 2003. Tree Structures for Mining association Rules. Journal of Data Mining and Knowledge Discovery, Vol 8, No 1, pp.25-51. [CrossRef] [Google Scholar]
- Forman, E.H., 1993. Facts and fictions about the analytic hierarchy process. Mathematical and Computer Modelling, Volume 17, Issues 4–5, pp.19-26. [CrossRef] [Google Scholar]
- Fournier-Viger, P., Gomariz, Gueniche, T., A., Soltani, A., Wu., C., Tseng, V. S. 2014. SPMF: a Java Open-Source Pattern Mining Library. Journal of Machine Learning Research (JMLR) 15, pp. 3389-3393. [Google Scholar]
- Han, J., Pei, J., Yin, Y. & Mao, R., 2004. Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach. Data Mining and Knowledge Discovery 8, pp.53–87. [CrossRef] [Google Scholar]
- Heydari, A., Tavakoli, M.A., Salim, N., & Heydari, Z., 2015. Detection of review spam: A survey. Expert Systems with Applications, 42(7), pp.3634–42. [CrossRef] [Google Scholar]
- Jindal, N., & Liu, B. 2008. Opinion Spam and Analysis. Proceedings WSDM ‘08 Proceedings of the 2008 International Conference on Web Search and Data Mining, 219-230. [Google Scholar]
- Khan, K., Baharudin, B., Khan, A., & Ullah, A., 2014. Mining opinion components from unstructured reviews: A review. Journal of King Saud University - Computer and Information Sciences, 26(3), pp.258–75. [CrossRef] [Google Scholar]
- Leskovec, J., Rajaraman, A. & Ullman, J.D., 2011. Mining of Massive Data Sets. Cambridge University Press. [Google Scholar]
- Liu, B., 2009. Opinion Mining. Encyclopedia of Database System, pp.1986–90. [Google Scholar]
- Liu, B., 2012. Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers. [Google Scholar]
- McAuley, J., & Leskovec, J. 2013. Hidden Factors and Hidden Topics : Understanding Rating Dimensions with Review Text. Proceeding RecSys ’13 Proceeding of the 7th ACM conference on Recommender Systems, 165-172. [Google Scholar]
- Pang, B. & Lee, L., 2008. Opinion Mining and Sentiment Analysis. Foundations and Trends in Information Retrieval Vol. 2, No 1-2, pp.1-135. [CrossRef] [Google Scholar]
- Ravi, K. & aRavi, V., 2015. A survey on opinion mining and sentiment analysis: Tasks, approaches and applications. Knowledge-Based Systems, 89, pp.14-46. [CrossRef] [Google Scholar]
- Sandhya, N., Lalitha, Y.S., Govardhan, A. & Anuradha, K., 2008. Analysis of Similarity Measures for Text Clustering. CSC Journals 2. [Google Scholar]
- Savage, D., Zhang, X., Yu, X., Chou, P., Wang, Q., 2015. Detection of opinion spam based on anomalous rating deviation. Expert Systems with Applications, 42(22), pp.8650–57. [CrossRef] [Google Scholar]
- Socher, R., Perelygin, A., Wu, J.Y., Chuang, J., Manning, C.D., Ng, A.Y., Potts, C., 2013. Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank. Proceedings of the conference on empirical methods in natural language processing (EMNLP). Vol. 1631, 1642. [Google Scholar]
- Wang, G., Xie, S., Liu, B., & Yu, P.S 2011. Review Graph Based Online Store Review Spammer Detection. Proceeding ICDM ‘11 Proceedings of the 2011 IEEE 11th International Conference on Data Mining, 1242-1247. [Google Scholar]
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