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In this paper we propose to apply an algorithm for finding out and cleaning mislabeled training sample in an adversarial learning context, in which a malicious user tries to camouflage training patterns in order to limit the classification system performance. In particular, we describe how this algorithm can be effectively applied to the problem of identifying HTTP traffic flowing through port TCP...
This paper describes our approach to adapting a text document similarity classifier based on the Term Frequency Inverse Document Frequency (TFIDF) metric to reconfigurable hardware. The TFIDF classifier is used to detect web attacks in HTTP data. In our reconfigurable hardware approach, we design a streaming, real-time classifier by simplifying an existing sequential algorithm and manipulating the...
Human often wants to listen to music that fits best his current emotion. A grasp of emotions in songs might be a great help for us to effectively discover music. In this paper, we aimed at automatically classifying moods of songs based on lyrics and metadata, and proposed several methods for supervised learning of classifiers. In future, we plan to use automatically identified moods of songs as metadata...
In this study, an article recommendation system for English reading comprehension improvement is proposed. The goal of this study is to find out the most important attributes that affect the difficulty of an article according to the levels granted by the General English Proficiency Test (GEPT). Using the determined attributes to classify the articles gathered by the crawler from the Internet everyday...
Port state control (PSC) inspection is the most important mechanism to ensure world marine safe. Recently, some SVM-based risk assessment systems have been presented in the world. They estimate the risk of each candidate ship based on its generic factors and history inspection factors to select high-risk one before conducting on-board PSC inspection. However, how to improve the performance of the...
In this paper, we present a scheme of steganalysis of JPEG images with the use of polynomial fitting and computational intelligence techniques. Based on the Generalized Gaussian Distribution (GGD) model in the quantized DCT coefficients, the errors between the logarithmic domain of the histogram of the DCT coefficients and the polynomial fitting are extracted as features to detect the adulterated...
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