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With the continuous development of Internet technology, accurate classification of network traffic becomes more and more important. Statistics-based traffic classification with extremely accuracy and high expansibility has become the mainstream of this domain. However, this method also has some shortcomings, such as, overabundance of statistical features, and insufficient flexibility of feature vector...
The automatic insertion of diacritics in electronic texts is necessary for a number of languages, including French, Romanian, Croatian, Sindhi, Vietnamese, etc. When diacritics are removed from a word and the resulting string of characters is not a word, it is easy to recover the diacritics. However, sometimes the resulting string is also a word, possibly with different grammatical properties or a...
The classification of unstructured P2P multicast video streaming is the premise for playing online linkage and real-time evidence in the process of network monitoring management. Based on the classification method in the preliminary research, an improved classification method is proposed. the method uses an optimal feature vector extraction algorithm to filter the proposed behavior features in the...
This study investigates the nearest neighbor classification of predicting Pareto dominance relationships in multi-objective optimization. A similarity measurement called the sum of ranked dimensional sequential number is proposed. It transfers the original domains of each decision components into the same integer interval [0:N-1], where N is the size of sample set. Each decision component of a sample...
We discuss an original approach to multidimensional non-stationary time series classification based on dynamic patterns analysis. The main problem in time series classification is construction of appropriate feature space. The success of classification dramatically depends on the quality of the feature space chosen. To construct this space we develop the method for extraction of dynamic patterns that...
Based on the research of layered semantic cognition, a new method of malicious code detection is proposed. With the ability of anti-aliasing, it can quickly identify the malicious code in the unknown program. Obtaining behavioral data via virtualizing the capture environment, implementing the hierarchical cognitive through abstracting layer by layer, and lastly, the method uses the Bayesian classifier...
Population of old generation that live alone is growing in most countries. Surveillance systems help them stay home and reduce the burden on the healthcare system. Automatic visual surveillance systems have advantages over wearable devices. They extract features from video sequences and use them for event classification. But these features are dependent on the position of cameras relative to the person...
In this paper, we proposed an approach to Musical Instrument Automatic Recognition. We used seven different musical instruments to be played simultaneously from solos to quartets. Our data have 296 feature vectors that used in audio signal classification by MLP neural networks and K-NN algorithm. Finally, MLP achieved as the best neural network in musical instrument recognition.
Spam has created a significant security problem for computer users everywhere. Spammers take an advantage of defrauds to cover parts of messages that can be used for identification of spam. For instance, a spammer does not need to consume much cost and bandwidth for sending junk mails even more than one hundred emails. On the other hand, from the feature selection perspective, one of the specific...
In this article we propose a differential evolution based nearest prototype classifier with extension to selecting the applied distance measure from a pool of alternative measures optimally for the particular data set at hand. The proposed method extends the earlier differential evolution based nearest prototype classifier by extending the optimization process to cover also the selection of distance...
A new method of feature extraction based on immune clonal selection algorithm is proposed, in which the immune clonal selection algorithm is used to optimize the projection vector. Some orthogonal bases are randomly selected as the initial basis vector sets from the original feature space, and the direction of the basis vectors is optimized to generate the optimal projection vector using the immune...
Aimed at the imbalance of training samples, isolated points, and the importance degree of class samples of different three questions, this paper put forward a improvement weighted support vector machine (SVM), and give the method of determine the integrated weights, the simulation results show the effectiveness of the method.
Online reviews of commercial sites are important sources for customers to obtain information and opinions by other customers. However, generally, the reviews contain several mixed information such as purpose and sentiments of reviewers. Therefore, when the reviews are classified automatically using some machine learning methods, it is necessary to construct adequate data preliminary for machine learning...
Peer-to-peer (P2P) networks are becoming more and more popular. eMule is a typical example. In this paper we aim to automatically and accurately find sensitive files in eMule through rating them based on text classification and we propose two feature expansion methods to improve the accuracy of rating. Experimental results demonstrate that the performance improvement of rating is significant by using...
Mangosteen export generates large revenue; however, translucent mangosteens, which contain undesirable internal condition, result in the shipment rejection and decrease the reliability of the export. This research investigates a novel non-destructive classification approach based on acoustic frequency response to detect mangosteens containing translucent fleshes. The set of uniform-distributed multi-frequency...
In this paper, we demonstrate a feature processing procedure which emphasizes on the combination of original features with redundancy trimming steps. This procedure shows better classification result than traditional classification models. In our experiment, several key feature processing steps were proposed according to the type od the feature. These steps contains numerical to categorical feature...
Two-dimensional feature extraction methods such as two-dimensional principal component analysis (2DPCA) and two-dimensional linear discriminant analysis (2DLDA) have been extensively studied in the past several years. Numerous experimental results demonstrate that these two-dimensional feature extraction methods are generally more efficient than and at least as effective as their one-dimensional counterparts...
Mouse dynamics, the analysis of individuals' distinctive mouse actions, has been proposed as a biometric to discriminate legitimate users from impostors. Some researchers have explored this domain and showed promising results, but few examined the effectiveness and applicability of this technique, particularly regarding the inconsistent evaluation conditions, unacceptably long authentication time,...
The paper presents how solving regression problems can be posed as finding solutions to multiclass classification tasks. The accuracy (averaged over several benchmarking data sets used in this study) of an approximating (hyper)surface to the data points over a given high-dimensional input space created by a nonlinear multiclass classifier is slightly superior to the solution obtained by regression...
Mouse-dynamics-related schemes have been shown to be feasible for user authentication systems, however, the existing approaches are either intrusive or not prompt response. Preventing unauthorized accesses to critical digital assets, namely, data stored in the file management system, is one of the major objectives of user authentication. We therefore propose a non-intrusive approach capable of verifying...
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