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Cluster Computing

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12-11-2017

A filtering of message in online social network using hybrid classifier

Authors: M. Srividya, M. S. Irfan Ahmed

Published in: Cluster Computing | Special Issue 5/2019

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Abstract

In emerging trend of society based on online social networking (OSN), it is useful for associative with social relationship. It is mainly used to share all moments via messages with their private and public sector. In this social network, most of the people used to send indecent text to others. So, non-essential text will be neglected from user to view desirable messages on their OSN walls. This paper explores the use of short text classifier includes latent semantic analysis for extracting meaningful text to present on their user wall by preventing useless messages. The proposed algorithm concerns hybrid combination of text classifiers such as support vector machine SVM–ELM, SVM–NAÏVE, NAÏVE–ELM, and NAÏVE–artificial neuro-fuzzy inference systems. Comparative study of these techniques contributes which will gives higher prediction accuracy in evaluation process.

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Adomavicius, A., Tuzhilin, G.: Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions. IEEE Trans. Knowl. Data Eng. 17(6), 734–749 (2005)CrossRef

Carminati, B., Ferrari, E., Binaghi, E., Vanetti, M., Carullo, M.: A system to filter unwanted messages from OSN user walls. IEEE Trans. Knowl. Data Eng. 25(2), 285–297 (2013)CrossRef

Kumar, H., Jain, S., Srivastava, R.: Risk analysis of online social networks. In: International Conference on Computing, Communication and Automation (ICCCA), pp. 846–851. IEEE (2016)

Li, J., Yan, H., Liu, Z.: Location-sharing systems with enhanced privacy in mobile online social networks. IEEE Syst. J. 11(2), 439–448 (2017)CrossRef

Liu, X.: An improved clustering-based collaborative filtering recommendation algorithm. Clust. Comput. 20(2), 1281–1288 (2017)CrossRef

Chau, M., Chen, H.: A machine learning approach to web page filtering using content and structure analysis. Decis. Support Syst. 44(2), 482–494 (2008)CrossRef

Joachims, T.: Text categorization with support vector machines: learning with many relevant features. In: European Conference on Machine Learning, pp. 137–142. ACM (1998)

Zhou, S., Guan, J.: Evaluation and construction of training corpuses for text classification: a preliminary study. In: International Conference on Application of Natural Language to Information System, pp. 97–108. Springer, Berlin (2002)

Joachims, T.: Text categorization with Support Vector Machines: learning with many relevant features. In: 10th European Conference on Machine Learning Chemnitz, pp. 137–142. Springer, Berlin (1998)

10.

Novovicova, J., Malik, A., Pudil, P.: Feature selection using improved mutual information for text classification. In: International Workshops on Statistical, Techniques, Structural and Syntactic Pattern Recognition, pp. 1010–1017. Springer, Berlin (2004)

11.

Vanetti, M., Binaghi, E., Carminati, B., Carullo, M., Ferrari, E.: Content-based filtering in online social networks. In: International Workshop on Privacy and Security Issues in Data Mining and Machine Learning (PSDML ’10). Springer, Berlin (2011)

12.

Cho, J.-H., Alsmadi, I., Xu, D.: Privacy and social capital in online social networks. In: IEEE Global Communications Conference (GLOBECOM), pp. 1–7. IEEE (2016)

13.

Bao, Y., Ishii, N.: Combining multiple KNN classifiers for text categorization by reducts. In: International Conference on Discovery Science, pp. 340–347. Springer, Berlin (2002)

14.

Nardiello, P., Sebastiani, F., Sperduti, A.: Discretizing continuous attributes in ada boost for text categorization. In: European Conference on Information Retrieval, pp. 320–334. Springer, Berlin (2003)

15.

Zeng, Y., Xing, L.: A study of online social network privacy via the TAPE framework. J. Sel. Top. Signal Process. 9(7), 1270–1284 (2015)CrossRef

16.

Sebastiani, F.: Machine learning in automated text categorization. Comput. Surv. 34(1), 1–47 (2002)MathSciNetCrossRef

17.

Paramasivam, S., Arumugam, R.: Accurate rotor position estimation for switched reluctance motor using ANFIS. In: Conference on Convergent Technologies for Asia–Pacific Region, vol. 4, pp. 1493–1497. IEEE (2003)

18.

Foltz, P.W., Dumais, S.T.: Personalized information delivery: analysis of information filtering methods. Spec. Issue Inf. Filter. 35(12), 51–60 (1992)

19.

Hull, D.: Improving text retrieval for the routing problem using latent semantic indexing. In: 17th Annual International Conference on Research and Development in Information Retrieval, pp. 282–291. ACM (1994)

20.

Han, X., Zu, G., Ohyama, W., Wakabayashi, T., Kimura, F.: Accuracy improvement of automatic text classification based on feature transformation and multi-classifier combination. In: Content Computing, pp. 463–468. Springer, Berlin (2004)

21.

Sebastiani, F.: Machine learning in automated text categorization. Comput. Surv. 34(1), 1–47 (2002)MathSciNetCrossRef

22.

Zu, G., Ohyama, W., Wakabayashi, T., Kimura, F.: Accuracy improvement of automatic text classification based on feature transformation. In: Proceedings of the ACM Symposium on Document Engineering, pp. 118–120. ACM (2003)

Title: A filtering of message in online social network using hybrid classifier
Authors: M. Srividya
M. S. Irfan Ahmed
Publication date: 12-11-2017
Publisher: Springer US
Published in: Cluster Computing / Issue Special Issue 5/2019
Print ISSN: 1386-7857
Electronic ISSN: 1573-7543
DOI: https://doi.org/10.1007/s10586-017-1300-y

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