The Community for Technology Leaders
RSS Icon
Issue No.02 - Feb. (2013 vol.25)
pp: 285-297
Marco Vanetti , University of Insubria, Varese
Elisabetta Binaghi , University of Insubria, Varese
Elena Ferrari , University of Insubria, Varese
Barbara Carminati , University of Insubria, Varese
Moreno Carullo , University of Insubria, Varese
One fundamental issue in today's Online Social Networks (OSNs) is to give users the ability to control the messages posted on their own private space to avoid that unwanted content is displayed. Up to now, OSNs provide little support to this requirement. To fill the gap, in this paper, we propose a system allowing OSN users to have a direct control on the messages posted on their walls. This is achieved through a flexible rule-based system, that allows users to customize the filtering criteria to be applied to their walls, and a Machine Learning-based soft classifier automatically labeling messages in support of content-based filtering.
Access control, Feature extraction, Facebook, Semantics, Text categorization, Graphical user interfaces, policy-based personalization, Online social networks, information filtering, short text classification
Marco Vanetti, Elisabetta Binaghi, Elena Ferrari, Barbara Carminati, Moreno Carullo, "A System to Filter Unwanted Messages from OSN User Walls", IEEE Transactions on Knowledge & Data Engineering, vol.25, no. 2, pp. 285-297, Feb. 2013, doi:10.1109/TKDE.2011.230
[1] 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.
[2] 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.
[3] 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.
[4] F. Sebastiani, "Machine Learning in Automated Text Categorization," ACM Computing Surveys, vol. 34, no. 1, pp. 1-47, 2002.
[5] 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.
[6] 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.
[7] P.J. Denning, "Electronic Junk," Comm. ACM, vol. 25, no. 3, pp. 163-165, 1982.
[8] 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.
[9] P.S. Jacobs and L.F. Rau, "Scisor: Extracting Information from On-Line News," Comm. ACM, vol. 33, no. 11, pp. 88-97, 1990.
[10] S. Pollock, "A Rule-Based Message Filtering System," ACM Trans. Office Information Systems, vol. 6, no. 3, pp. 232-254, 1988.
[11] P.E. Baclace, "Competitive Agents for Information Filtering," Comm. ACM, vol. 35, no. 12, p. 50, 1992.
[12] 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.
[13] G. Amati and F. Crestani, "Probabilistic Learning for Selective Dissemination of Information," Information Processing and Management, vol. 35, no. 5, pp. 633-654, 1999.
[14] 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.
[15] 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.
[16] 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.
[17] 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.
[18] D.D. Lewis, "An Evaluation of Phrasal and Clustered Representations on a Text Categorization Task," Proc. 15th ACM Int'l Conf. Research and Development in Information Retrieval (SIGIR '92), N.J. Belkin, P. Ingwersen, and A.M. Pejtersen, eds., pp. 37-50, 1992.
[19] R.E. Schapire and Y. Singer, "Boostexter: A Boosting-Based System for Text Categorization," Machine Learning, vol. 39, nos. 2/3, pp. 135-168, 2000.
[20] H. Schütze, D.A. Hull, and J.O. Pedersen, "A Comparison of Classifiers and Document Representations for the Routing Problem," Proc. 18th Ann. ACM/SIGIR Conf. Research and Development in Information Retrieval , pp. 229-237, 1995.
[21] E.D. Wiener, J.O. Pedersen, and A.S. Weigend, "A Neural Network Approach to Topic Spotting," Proc. Fourth Ann. Symp. Document Analysis and Information Retrieval (SDAIR '95), pp. 317-332, 1995.
[22] T. Joachims, "Text Categorization with Support Vector Machines: Learning with Many Relevant Features," Proc. European Conf. Machine Learning, pp. 137-142, 1998.
[23] T. Joachims, "A Probabilistic Analysis of the Rocchio Algorithm with TFIDF for Text Categorization," Proc. Int'l Conf. Machine Learning, pp. 143-151, 1997.
[24] S.E. Robertson and K.S. Jones, "Relevance Weighting of Search Terms," J. Am. Soc. for Information Science, vol. 27, no. 3, pp. 129-146, 1976.
[25] S. Zelikovitz and H. Hirsh, "Improving Short Text Classification Using Unlabeled Background Knowledge," Proc. 17th Int'l Conf. Machine Learning (ICML '00), P. Langley, ed., pp. 1183-1190, 2000.
[26] V. Bobicev and M. Sokolova, "An Effective and Robust Method for Short Text Classification," Proc. 23rd Nat'l Conf. Artificial Intelligence (AAAI), D. Fox and C.P. Gomes, eds., pp. 1444-1445, 2008.
[27] B. Sriram, D. Fuhry, E. Demir, H. Ferhatosmanoglu, and M. Demirbas, "Short Text Classification in Twitter to Improve Information Filtering," Proc. 33rd Int'l ACM SIGIR Conf. Research and Development in Information Retrieval (SIGIR '10), pp. 841-842, 2010.
[28] J. Golbeck, "Combining Provenance with Trust in Social Networks for Semantic Web Content Filtering," Proc. Int'l Conf. Provenance and Annotation of Data, L. Moreau and I. Foster, eds., pp. 101-108, 2006.
[29] F. Bonchi and E. Ferrari, Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques. Chapman and Hall/CRC Press, 2010.
[30] A. Uszok, J.M. Bradshaw, M. Johnson, R. Jeffers, A. Tate, J. Dalton, and S. Aitken, "Kaos Policy Management for Semantic Web Services," IEEE Intelligent Systems, vol. 19, no. 4, pp. 32-41, July/Aug. 2004.
[31] L. Kagal, M. Paolucci, N. Srinivasan, G. Denker, T. Finin, and K. Sycara, "Authorization and Privacy for Semantic Web Services," IEEE Intelligent Systems, vol. 19, no. 4, pp. 50-56, July 2004.
[32] P. Bonatti and D. Olmedilla, "Driving and Monitoring Provisional Trust Negotiation with Metapolicies," Proc. Sixth IEEE Int'l Workshop Policies for Distributed Systems and Networks (POLICY '05), pp. 14-23, 2005.
[33] C. Bizer and R. Cyganiak, "Quality-Driven Information Filtering Using the Wiqa Policy Framework," Web Semantics: Science, Services and Agents on the World Wide Web, vol. 7, pp. 1-10, Jan. 2009.
[34] D.D. Lewis, Y. Yang, T.G. Rose, and F. Li, "Rcv1: A New Benchmark Collection for Text Categorization Research," J. Machine Learning Research, vol. 5, pp. 361-397, 2004.
[35] M. Carullo, E. Binaghi, and I. Gallo, "An Online Document Clustering Technique for Short Web Contents," Pattern Recognition Letters, vol. 30, pp. 870-876, July 2009.
[36] M. Carullo, E. Binaghi, I. Gallo, and N. Lamberti, "Clustering of Short Commercial Documents for the Web," Proc. 19th Int'l Conf. Pattern Recognition (ICPR '08), 2008.
[37] C.D. Manning, P. Raghavan, and H. Schütze, Introduction to Information Retrieval. Cambridge Univ. Press, 2008.
[38] G. Salton and C. Buckley, "Term-Weighting Approaches in Automatic Text Retrieval," Information Processing and Management, vol. 24, no. 5, pp. 513-523, 1988.
[39] J. Moody and C. Darken, "Fast Learning in Networks of Locally-Tuned Processing Units," Neural Computation, vol. 1, no. 2, pp. 281-294, 1989.
[40] M.J.D. Powell, "Radial Basis Functions for Multivariable Interpolation: A Review," Algorithms for Approximation, pp. 143-167, Clarendon Press, 1987.
[41] E.J. Hartman, J.D. Keeler, and J.M. Kowalski, "Layered Neural Networks with Gaussian Hidden Units as Universal Approximations," Neural Computation, vol. 2, pp. 210-215, 1990.
[42] J. Park and I.W. Sandberg, "Approximation and Radial-Basis-Function Networks," Neural Computation, vol. 5, pp. 305-316, 1993.
[43] A.K. Jain, R.P.W. Duin, and J. Mao, "Statistical Pattern Recognition: A Review," IEEE Trans. Pattern Analysis and Machine Intelligence, vol. 22, no. 1, pp. 4-37, Jan. 2000.
[44] C. Cleverdon, "Optimizing Convenient Online Access to Bibliographic Databases," Information Services and Use, vol. 4, no. 1, pp. 37-47, 1984.
[45] J.A. Golbeck, "Computing and Applying Trust in Web-Based Social Networks," PhD dissertation, Graduate School of the Univ. of Maryland, College Park, 2005.
[46] J.L. Chameau and J.C. Santamarina, "Membership Functions I: Comparing Methods of Measurement," Int'l J. Approximate Reasoning, vol. 1, pp. 287-301, 1987.
[47] V. Leekwijck and W. Kerre, "Defuzzification: Criteria and Classification," Fuzzy Sets and Systems, vol. 108, pp. 159-178, 1999.
[48] J.R. Landis and G.G. Koch, "The Measurement of Observer Agreement for Categorical Data," Biometrics, vol. 33, no. 1, pp. 159-174, Mar. 1977.
[49] Information Retrieval: Data Structures & Algorithms, W.B. Frakes and R.A. Baeza-Yates, eds., Prentice-Hall, 1992.
[50] A. Laudanna, A.M. Thornton, G. Brown, C. Burani, and L. Marconi, "Un Corpus Dell'Italiano Scritto Contemporaneo Dalla Parte Del Ricevente," III Giornate internazionali di Analisi Statistica dei Dati Testuali, vol. 1, pp. 103-109, 1995.
[51] U. Hanani, B. Shapira, and P. Shoval, "Information Filtering: Overview of Issues, Research and Systems," User Modeling and User-Adapted Interaction, vol. 11, pp. 203-259, 2001.
[52] J. Nin, B. Carminati, E. Ferrari, and V. Torra, "Computing Reputation for Collaborative Private Networks," Proc. 33rd Ann. IEEE Int'l Computer Software and Applications Conf., vol. 1, pp. 246-253, 2009.
[53] K. Strater and H. Richter, "Examining Privacy and Disclosure in a Social Networking Community," Proc. Third Symp. Usable Privacy and Security (SOUPS '07), pp. 157-158, 2007.
[54] L. Fang and K. LeFevre, "Privacy Wizards for Social Networking Sites," Proc. 19th Int'l Conf. World Wide Web (WWW '10), pp. 351-360, 2010.
70 ms
(Ver 2.0)

Marketing Automation Platform Marketing Automation Tool