Open Access
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
Published online 23 May 2016
  1. 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]
  2. 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]
  3. 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.
  4. 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]
  5. 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]
  6. 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.
  7. 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]
  8. Leskovec, J., Rajaraman, A. & Ullman, J.D., 2011. Mining of Massive Data Sets. Cambridge University Press.
  9. Liu, B., 2009. Opinion Mining. Encyclopedia of Database System, pp.1986–90.
  10. Liu, B., 2012. Sentiment Analysis and Opinion Mining. Morgan & Claypool Publishers.
  11. 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.
  12. 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]
  13. 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]
  14. Sandhya, N., Lalitha, Y.S., Govardhan, A. & Anuradha, K., 2008. Analysis of Similarity Measures for Text Clustering. CSC Journals 2.
  15. 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]
  16. 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.
  17. 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.

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