Spam Filtering in Social Networks Using Regularized Deep Neural Networks with Ensemble Learning - Artificial Intelligence Applications and Innovations (AIAI 2018) Access content directly
Conference Papers Year : 2018

Spam Filtering in Social Networks Using Regularized Deep Neural Networks with Ensemble Learning

Aliaksandr Barushka
  • Function : Author
  • PersonId : 1033474
Petr Hájek
  • Function : Author
  • PersonId : 992409

Abstract

Spam filtering in social networks is increasingly important owing to the rapid growth of social network user base. Sophisticated spam filters must be developed to deal with this complex problem. Traditional machine learning approaches such as neural networks, support vector machine and Naïve Bayes classifiers are not effective enough to process and utilize complex features present in high-dimensional data on social network spam. To overcome this problem, here we propose a novel approach to social network spam filtering. The approach uses ensemble learning techniques with regularized deep neural networks as base learners. We demonstrate that this approach is effective for social network spam filtering on a benchmark dataset in terms of accuracy and area under ROC. In addition, solid performance is achieved in terms of false negative and false positive rates. We also show that the proposed approach outperforms other popular algorithms used in spam filtering, such as decision trees, Naïve Bayes, artificial immune systems, support vector machines, etc.
Fichier principal
Vignette du fichier
467708_1_En_4_Chapter.pdf (791.93 Ko) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-01821042 , version 1 (22-06-2018)

Licence

Attribution

Identifiers

Cite

Aliaksandr Barushka, Petr Hájek. Spam Filtering in Social Networks Using Regularized Deep Neural Networks with Ensemble Learning. 14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), May 2018, Rhodes, Greece. pp.38-49, ⟨10.1007/978-3-319-92007-8_4⟩. ⟨hal-01821042⟩
120 View
85 Download

Altmetric

Share

Gmail Facebook X LinkedIn More