Automatic violent content web filtering approach based on the KDD process

International Journal of Web Information Systems

Volumn 4, Issue 4, 2008, Pages 441-464

  Hammami, Mohamed ^a   Guermazi, Radhouane ^a   Hamadou, Abdelmajid Ben ^a  

^a UNIVERSITY OF SFAX   (Tunisia)

Author keywords

Classification schemes; Content management; Data analysis; Worldwide web

Indexed keywords

CLASSIFICATION ACCURACY; CLASSIFICATION SCHEME; COMPARATIVE STUDIES; CONTENT MANAGEMENT; CONTENT-BASED ANALYSIS; DESIGN/METHODOLOGY/APPROACH; FILTERING SYSTEMS; INTERNET ACCESS;

CLASSIFICATION (OF INFORMATION); DATA MINING; DATA REDUCTION; DECISION TREES; ELECTRONIC DOCUMENT EXCHANGE; WEBSITES;

INFORMATION RETRIEVAL SYSTEMS;

EID: 84886415355     PISSN: 17440084     EISSN: None     Source Type: Journal    
DOI: 10.1108/17440080810919486     Document Type: Article

References (27)

1. Arentz, W.A. and Olstad, B. (2004), "Classifying offensive sites based on image content,", Computer Vision and Image Understanding, Vol. 94, pp. 295-310.
2. Caulkins, J.P., Ding, W., Duncan, G., Krishnan, R. and Nyberg, E. (2006), "A method for managing access to web pages: filtering by statistical classification (fsc) applied to text,", Decision Support Systems, Vol. 42, pp. 144-61, Classifying offensive sites based on image content. (Pubitemid 44278271)
3. Clech, J., Rakotomalala, R. and Jalam, R. (2003), "Sé léction multivariée de termes,", XXXVmes Journes de Statistique, pp. 933-9.
4. Denoyer, L., Vittaut, J.N., Gallinari, P. and Brunessaux, S. (2003), "Structured multimedia document classification,", ACM Symposium on Document Engineering, Vol. 2, pp. 153-60.
5. Dreyfus, G. (2005), Neural Networks Methodology and Applications, Springer, Berlin.
6. Du, R., Naini, R.S. and Susilon, W. (2003), "Web filtering using text classification,", IEEE International Conference on Networks, pp. 325-30.
7. Fayyad, U., Piatetsky-Shapirop, G. and Smyth, P. (1996), "The KDD process for extracting useful knowledge from volumes data,", Communication of the ACM, Vol. 39 No. 11, pp. 27-34. (Pubitemid 126428076)
8. Glover, E.J., Tsioutsiouliklis, K., Lawrence, S., Pennock, D.M. and Flake, G.W. (2002), "Using web structure for classifying and describing web pages,", paper presented at International World Wide Web Conference, pp. 562-9.
9. Grefenstette, G. (1995), "Comparing two language identification schemes,", paper presented at International Conference on the Statistical Analysis of Textual Data, pp. 263-8.
10. Grilhers, B., Brunessaux, S. and Leray, P. (2004), "Combining classifiers for harmful document filtering,", paper presented at RIAO'2004, Coupling Approaches, Coupling Media and Coupling Languages for Information Retrieval, pp. 1-10.
11. Guermazi, R., Hammami, M. and Ben-Hamadou, A. (2007), "Filtrage des sites Web à caractère violent par analyse du contenu textuel et structurel,", ECG, pp. 343-54.
12. Hammami, M. and Chen, L. (2005), "Web adult content detection and filtering system,", International Journal of Business Data Communications and Networking, Vol. 1 No. 1, pp. 17-32.
13. Hammami, M., Chahir, Y. and Chen, L. (2006), "A web filtering engine combining textual, structural, and visual content-based analysis,", IEEE Transactions on Knowledge and Data Engineering, Vol. 18 No. 2, pp. 272-84.
14. Haykin, S. (1998), Neural Networks - A Comprehensive Foundation, 2nd ed., Prentice-Hall, Englewood Cliffs, NJ.
15. Ho, W.H. and Watters, P.A. (2004), "Statistical and structural approaches to filtering internet pornography,", IEEE Conference on Systems, Man and Cybernetics, Vol. 5, pp. 4792-8. (Pubitemid 40415784)
16. Jalam, R., Chauchat, J-H. and Dumais, J. (2004), "Automatic recognition of characteristic keywords using n-grams,", paper presented at International Conference on Computational Statistics, pp. 1245-54.
17. Lee, P.Y., Hui, S.C. and Fong, A.C.M. (2002), "Neural networks for web content filtering,", IEEE Intelligent Systems, Vol. 17 No. 5, pp. 48-57.
18. Miller, E., Shen, D., Liu, J. and Nicholas, C. (2000), "Performance and scalability of a large-scale n-gram based information retrieval system,", Journal of Digital Information, Vol. 1 No. 21.
19. Quinlan, J.R. (1986), "Induction of decision trees,", Machine Learning, Vol. 1, pp. 81-106.
20. Quinlan, J.R. (1993), "C4.5: programs for machine learning,", Morgan Kaufmann, San Mateo, CA.
21. Rakotomalala, R. and Lallich, S. (1998), "Handling noise with generalized entropy of type beta in induction graphs algorithm,", paper presented at International Conference on Computer Science and Informatics, pp. 25-7.
22. Rao, M.A. and Srinivas, J. (2003), Neural Networks: Algorithms and Applications, Alpha Science International Ltd, Oxford.
23. Schlkopf, B., Burges, C. and Smola, A.J. (1999), Advances in Kernel Methods Support Vector Learning, MIT Press, Cambridge, MA.
24. Su, G-y., Li, J-h., Ma, Y-h. and Li, S-h. (2004), "Improving the precision of the keyword-matching pornographic text filtering method using a hybrid model,", Journal of Zhejiang University Science, Vol. 5 No. 9, pp. 1106-13. (Pubitemid 40017121)
25. Vinot, R., Grabar, N. and Valette, M. (2003), "Applications d'algorithmes de classification automatique pour la détection des contenus racistes sur l'Internet,", Traitement Automatique des Langues Naturelles, Vol. 257, p. 284.
26. Zighed, D.A. and Rakotomalala, R. (1996), "A method for non arborescent induction graphs,", Technical report, Laboratory ERIC, University of Lyon, Lyon, p. 2.
27. Zighed, D.A. and Rakotomalala, R. (2000), Graphes d'Induction - Apprentissage et Data Mining, Hermes, Paris.