Abstract
A method for filtering spam blogs (splogs) based on a machine learning technique, and its evaluation results are described. Today, spam blogs (splogs) became one of major issues on the Web. The problem of splogs is that values of blog sites are different by people. We propose a novel user-oriented splog filtering method that can adapt each user’s preference for valuable blogs. We use the SVM(Support Vector Machine) for creating a personalized splog filter for each user. We had two experiments: (1) an experiment of individual splog judgement, and (2) an experiment for user oriented splog filtering. From the former experiment, we found existence of ‘gray’ blogs that are needed to treat by persons. From the latter experiment, we found that we can provide appropriate personalized filters by choosing the best feature set for each user. An overview of proposed method, and evaluation results are described.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Kolari, P., Java, A., Finin, T., Oates, T., Joshi, A.: Detecting spam blogs: A machine learning approach. In: Proceedings of the 21st National Conference on Association for Advancement of Artificial Intelligence (AAAI 2006), pp. 1351–1356 (2006)
Drucker, H., Wu, D., Vapnik, V.: Support vector machines for spam categorization. IEEE Transactions on Neural Networks, 1048–1054 (1999)
Ishida, K.: Extracting spam blogs with co-citation clusters. In: Proceedings of the 17th International Conference on World Wide Web (WWW 2008), pp. 1043–1044 (2008)
Junejo, K.N., Karim, A.: PSSF: A novel statistical approach for personalized service-side spam filtering. In: Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence (WI 2007), pp. 228–234 (2007)
Jeh, G., Widom, J.: Scaling personalized web search. In: Proceedings of the 12th International Conference on World Wide Web (WWW 2003), pp. 271–279 (2003)
Manning, C.D., Shuetze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge (1999)
Yoshinaka, T., Fukuhara, T., Masuda, H., Nakagawa, H.: A user-oriented splog filtering based on machine learning method- (in japanese). In: Proceedings of The 23rd Annual Conference on the Japanese Society for Artificial Intelligence (JSAI 2009), vol. 2B2-4 (2009)
Manning, C.D., Shuetze, H.: Foundations of Statistical Natural Language Processing. MIT Press, Cambridge (1999)
Wang, Y.M., Ma, M., Niu, Y., Chen, H.: Spam double-funnel: connecting web spammers with advertisers. In: Proceedings of the 16th International Conference on World Wide Web (WWW 2007), pp. 291–300 (2007)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yoshinaka, T., Ishii, S., Fukuhara, T., Masuda, H., Nakagawa, H. (2010). A User-Oriented Splog Filtering Based on a Machine Learning. In: Breslin, J.G., Burg, T.N., Kim, HG., Raftery, T., Schmidt, JH. (eds) Recent Trends and Developments in Social Software. BlogTalk BlogTalk 2008 2009. Lecture Notes in Computer Science, vol 6045. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16581-8_9
Download citation
DOI: https://doi.org/10.1007/978-3-642-16581-8_9
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-16580-1
Online ISBN: 978-3-642-16581-8
eBook Packages: Computer ScienceComputer Science (R0)