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Call for Paper - May 2015 Edition
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A Review on Filter Undesired Text from Social Networks

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International Journal of Computer Applications
© 2014 by IJCA Journal
Volume 107 - Number 14
Year of Publication: 2014
Authors:
Ujwala S. Tambe
Archana S. Vaidya
10.5120/18819-0227

Ujwala S.tambe and Archana S Vaidya. Article: A Review on Filter Undesired Text from Social Networks. International Journal of Computer Applications 107(14):15-18, December 2014. Full text available. BibTeX

@article{key:article,
	author = {Ujwala S.tambe and Archana S. Vaidya},
	title = {Article: A Review on Filter Undesired Text from Social Networks},
	journal = {International Journal of Computer Applications},
	year = {2014},
	volume = {107},
	number = {14},
	pages = {15-18},
	month = {December},
	note = {Full text available}
}

Abstract

Online social Network (OSN) is a social networking service which is a platform to build relations among people who share comfort, actions, backgrounds or real-life connections. Hundreds of thousands of people are using these social networking services for personal use, marketing. Entertainment, Business purpose. User security is the main issue in present days from person to person interaction. Message filtering is main task of proposed system. An online social network provides the little support to the user to avoid unwanted messages displayed on their own private space. In this paper, we propose system which gives ability to user to control the unwanted messages posted on their wall. To filter undesired messages propose three tier architecture containing message classifier based on content and using machine learning techniques. User is able to customize the filtering rule as per his/her preferences. i. e grant access to allow user to insert messages on his/her wall.

References

  • Vanetti, Elisabetta Binaghi, Elena Ferrari, Barbara Carminati, Moreno Carullo Department of Computer and Communication, University of Insubria "a system to filter out unwanted messages walls OSN user" IEEE Transactions on Knowledge And Engineering Flight Data: 25 Year 2013.
  • F. Sebastiani, "Machine learning in automated text categorization," ACM Computing Surveys, vol. 34, no. 1, pp. 1–47, 2002. J. Leskovec, D. P. Huttenlocher, and J. M. Kleinberg, "Predicting positive and negative links in online social networks," inProc. 19th Int. Conf. World Wide Web, 2010, pp. 641-650.
  • Vinaitheerthan Renganathan1*, Ajit N Babu2 and Suptendra Nath Sarbadhikari3 " A Tutorial on Information Filtering Concepts and Methods for Bio-medical Searching".
  • B. Sriram, D. Fuhry, E. Demir, H. Ferhatosmanoglu, and M. Demirbas,"Short text classification in twitter to improve information filtering," in Proceeding of the 33rd International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2010, 2010, pp. 841–842.
  • J. Golbeck, "Combining provenance with trust in social networks for semantic web content filtering," in Provenance and Annotation of Data, ser. Lecture Notes in Computer Science, L. Moreau and I. Foster, Eds. Springer Berlin / Heidelberg, 2006, vol. 4145, pp. 101–108.
  • P. J. Hayes, P. M. Andersen, I. B. Nirenburg, and L. M. Schmandt,"Tcs: a shell for content-based text categorization," in Proceedings of 6th IEEE Conference on Artificial Intelligence Applications (CAIA-90). IEEE Computer Society Press, Los Alamitos, US, 1990, pp. 320–326.
  • N. J. Belkin and W. B. Croft, "Information filtering and information retrieval: Two sides of the same coin?" Communications of the ACM, vol. 35, no. 12, pp. 29–38, 1992.
  • P. W. Foltz and S. T. Dumais, "Personalized information delivery: An analysis of information filtering methods," Communications of the ACM, vol. 35, no. 12, pp. 51–60, 1992.
  • S. Zelikovitz and H. Hirsh, "Improving short text classification using unlabeled background knowledge," in Proceedings of 17th International Conference on Machine Learning (ICML-00), P. Langley, Ed. Stanford, US: Morgan Kaufmann Publishers, San Francisco, US,2000, pp. 1183–1190.
  • V. Bobicev and M. Sokolova, "An effective and robust method for short text classification," in AAAI, D. Fox and C. P. Gomes, Eds. AAAI Press, 2008, pp. 1444–1445.
  • Pennock DM, Horvitz E, Lawrence S, Giles CL (2000) Collaborative filtering by personality diagnosis: A hybrid memory-and model-based approach. Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence (UAI-2000), Morgan Kaufmann Publishers Inc 473-480.
  • Boger Z, Kuflik T, Shapira B, Shoval P (2000) Information filtering and automatic keyword identification by artifical neural networks. Proceedings of the 8th European Conference on Information Systems.
  • Jennings A, Higuchi H (1993) A user model neural network for a personal news service. User Modeling and User-Adapted Interaction 3: 1-25.
  • S. Venkata Lakshmi, K. Hema "Filtering Information for Short Text Using OSN" International Journal of Advanced Research in Computer Science & Technology (IJARCST 2014)317 Vol. 2, Issue 2, Ver. 2