A NEW STRATEGY FOR DRIBBLING ANNOYED MESSAGES FROM ONLINE SOCIAL NETWORK

Madhava Raju Chintapalli, G. Srinivas

Abstract


A NEW STRATEGY FOR DRIBBLING ANNOYED MESSAGES FROM ONLINE SOCIAL NETWORK

Keywords


information filtering, short text classification, policy-based personalization.

References


A. Adomavicius and G. Tuzhilin, “Toward the Next Generation of Recommender Systems: A Survey of the State-of-the-Art and Possible Extensions,” IEEE Trans. Knowledge and Data Eng., vol. 17, no. 6, pp. 734-749, June 2005.

M. Chau and H. Chen, “A Machine Learning Approach to Web Page Filtering Using Content and Structure Analysis,” Decision Support Systems, vol. 44, no. 2, pp. 482-494, 2008.

R.J. Mooney and L. Roy, “Content-Based Book Recommending Using Learning for Text Categorization,” Proc. Fifth ACM Conf. Digital Libraries, pp. 195-204, 2000.

F. Sebastiani, “Machine Learning in Automated Text Categorization,” ACM Computing Surveys, vol. 34, no. 1, pp. 1-47, 2002.

M. Vanetti, E. Binaghi, B. Carminati, M. Carullo, and E. Ferrari, “Content-Based Filtering in On-Line Social Networks,” Proc. ECML/PKDD Workshop Privacy and Security Issues in Data Mining and Machine Learning (PSDML ’10), 2010.

N.J. Belkin and W.B. Croft, “Information Filtering and Information Retrieval: Two Sides of the Same Coin?” Comm. ACM, vol. 35, no. 12, pp. 29-38, 1992.

P.J. Denning, “Electronic Junk,” Comm. ACM, vol. 25, no. 3, pp. 163-165, 1982.

P.W. Foltz and S.T. Dumais, “Personalized Information Delivery: An Analysis of Information Filtering Methods,” Comm. ACM, vol. 35, no. 12, pp. 51-60, 1992.

P.S. Jacobs and L.F. Rau, “Scisor: Extracting Information from On- Line News,” Comm. ACM, vol. 33, no. 11, pp. 88-97, 1990.

S. Pollock, “A Rule-Based Message Filtering System,” ACM Trans. Office Information Systems, vol. 6, no. 3, pp. 232-254, 1988.

P.E. Baclace, “Competitive Agents for Information Filtering,” Comm. ACM, vol. 35, no. 12, p. 50, 1992.

P.J. Hayes, P.M. Andersen, I.B. Nirenburg, and L.M. Schmandt, “Tcs: A Shell for Content-Based Text Categorization,” Proc. Sixth IEEE Conf. Artificial Intelligence Applications (CAIA ’90), pp. 320- 326, 1990.

G. Amati and F. Crestani, “Probabilistic Learning for Selective Dissemination of Information,” Information Processing and Management, vol. 35, no. 5, pp. 633-654, 1999.

M.J. Pazzani and D. Billsus, “Learning and Revising User Profiles: The Identification of Interesting Web Sites,” Machine Learning, vol. 27, no. 3, pp. 313-331, 1997.

Y. Zhang and J. Callan, “Maximum Likelihood Estimation for Filtering Thresholds,” Proc. 24th Ann. Int’l ACM SIGIR Conf. Research and Development in Information Retrieval, pp. 294-302, 2001.

C. Apte, F. Damerau, S.M. Weiss, D. Sholom, and M. Weiss, “Automated Learning of Decision Rules for Text Categorization,” Trans. Information Systems, vol. 12, no. 3, pp. 233-251, 1994.

S. Dumais, J. Platt, D. Heckerman, and M. Sahami, “Inductive Learning Algorithms and Representations for Text Categorization,” Proc. Seventh Int’l Conf. Information and Knowledge Management (CIKM ’98), pp. 148-155, 1998.


Refbacks

  • There are currently no refbacks.




Copyright © 2012 - 2023, All rights reserved.| ijitr.com

Creative Commons License
International Journal of Innovative Technology and Research is licensed under a Creative Commons Attribution 3.0 Unported License.Based on a work at IJITR , Permissions beyond the scope of this license may be available at http://creativecommons.org/licenses/by/3.0/deed.en_GB.