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In recommender systems, numerous efforts have been made on utilizing textual information in matrix factorization to alleviate the problem of data sparsity. Recently, some of the works have explored neural networks to go for an in-depth understanding of textual item content, and further generate more accurate item latent models. These works achieve impressive effectiveness on performing recommendations...
This paper presents a budgetary learning algorithm for online multiclass classification. Based on the multiclass passive-aggressive learning with kernels, we introduce a dual perspective that gives rise to the proposed budgetary algorithm. Basically, the proposed algorithm limits the amount of data in use and fully exploits the available data on hand through optimization. The algorithm has both constant...
Existing traffic replay methods are mainly aim to generate a large number of network traffic per unit time, which neglect the time's authenticity of replay traffic. In order to generate the network traffic which is exactly the same as the real traffic in the target network, including packet's numbers, payloads, interactive orders and time series, this paper proposes a traffic replay method based on...
This paper presents an approach for unsupervised image categorization which can be used in non-label image library. We extract the basic feature from image, and by using bag of words model and spatial pyramid matching we manage to improve image descriptor performance. To get better clustering performance we propose an improved spectral clustering approach and use it to achieve our image categorization...
This paper presents a rigorous compositional semantics for SADF (Scenario-Aware Data Flow), an extension of SDF for scenario-based embedded system design which has its roots in digital signal processing. We show that Markov automata (MA), a novel combination of probabilistic automata and continuous-time Markov decision processes, provides a natural semantics when all execution times are exponential...
Because of the lack of interactivity in E-learning, the design ideas are proposed to build a 3D interactive virtual learning environment which is built based on OpenSim platform-an open source virtual reality platform in the paper. The architecture of OpenSim platform is introduced, the development process of a 3D interactive virtual learning environment is summarized based on OpenSim platform, and...
With the rapid development of virtual reality technology, the distributed virtual reality platform is becoming more modular and more standardized. Plugin technology based on reuse of software is widely used in distributed virtual reality platform. According to the basic principles of plug-in technology, OpenSim platform which is a distributed virtual reality platform based on an open source is analyzed,...
A new method of identifying bus faults based on support vector machine is proposed. First PSCAD/EMTDC is used to simulate the bus fault state,and then a support vector machine model is established after extracting Simulation Data, carrying out data pretreatment. Different kernel functions is used to train respectively for determining internal fault, external fault of bus and correct identification...
A new method to distinguish various fault types of transformer by differential protection based on LIBSVM is discussed. This paper uses PSCAD/EMTDC to build transformer and differential protection model which is applied to simulate various transformer fault types, the simulation data and characteristic value extracted are preprocessed; then fault identification model based on LIBSVM is established...
Our solution builds on a kernel-based method called the support vector machine (SVM) for determining the locations of the nodes. The basic SVM algorithm contains two steps: (1) one-region classification using the SVM; and (2) multi-region localization which is a repeated application of one-region classification for a number of different regions. In this paper, we first analyze the error effects of...
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