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8th IFIP International Conference on intelligent information processing, IIP 2014

作者： Qi, Baoyuan Ma, Gang Shi, Zhongzhi Wang, Wei Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing100190 China University of Chinese Academy of Sciences Beijing100190 China Beijing Lexo Technologies Co. Ltd Beijing100080 China

ISBN: (纸本)9783662449790

It has become a challenging work to collect valuable information from fast text streams. In this work, we propose a method which gains useful information effectively and efficiently. Firstly, we maintain an analyzer based on the Trie structure and the dynamic N-Gram tokenizer;secondly, unlike the traditional search engine principle, we consider the documents as a query by building the indexes for the whole query base. The experimental results show that it has the strong adaption ability, low latency and high quality support for the complex query combination compared with the conventional methods. © IFIP International Federation for information processing 2014.

关键词： Search engines

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A comparative study on artificial neural networks for environmental quality assessment

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Computer Modelling and New Technologies 2014年第7期18卷 41-47页

作者： Liu, Yijun He, Sheng Wang, Yao Wang, Xiumei Key laboratory of cloud computing and intelligent information processing of Changzhou City Jiangsu University of Technology China

The aim of this study is to use neural network tools as an environmental decision support in assessing environmental quality. A three-layer feedforward neural network using three learning approaches of BP, LM and GA-BP has been applied in non-linear modelling for the problem of environmental quality assessment. The case study shows that the well designed and trained neural networks are effective and form a useful tool for the prediction of environmental quality. Furthermore, the LM network has the fastest convergence speed and the GA-BP network outperforms the other two networks in both predictive and final classification accuracies of environmental quality.

关键词： Neural network models

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A group key distribution system based on the generalized aryabhata remainder theorem for enterprise digital rights management

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Journal of information Hiding and Multimedia Signal processing 2015年第1期6卷 140-153页

作者： Liu, Yanjun Chang, Chin-Chen Chang, Shih-Chang Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University No.111 Jiulong Rd Hefei230601 China Department of Computer Science and Information Engineering Asia University No.500 Lioufeng Rd Wufeng Taichung413 Taiwan Department of Information Engineering and Computer Science Feng Chia University No.100 Wenhwa Rd Seatwen Taichung407 Taiwan Department of Computer Science and Information Engineering National Chung Cheng University No.168 Sec.1 University Rd Min-Hsiung Township Chiayi621 Taiwan

Digital Rights Management (DRM) is a type of access-control technology that is used by diverse content providers to restrict the use of digital content. Enterprise Digital Rights Management (E-DRM) is an application of DRM techniques for managing the control of access to sensitive documents in an enterprise. In this paper, we propose a group key distribution system for E-DRM based on the concept of a secret-sharing mechanism and the generalized Aryabhata remainder theorem (GART). To the best of our knowledge, no previous publications related to E-DRM technologies have presented the group key distribution system that we propose. In our system, different groups of enterprise members within the enterprise obtain different digital content in parallel without collision by using their group’s unique session key;all members within each group share a common session key to decrypt the same digital documents to acquire the correct content. We proved that our system achieves the goal of providing high security, which includes preventing inside and outside attacks and offering forward and backward secrecy. © 2015.

关键词： Copyrights

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Online Chinese-Vietnamese bilingual topic detection based on RCRP algorithm with event elements 3

Online Chinese-Vietnamese bilingual topic detection based on...

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3rd CCF Conference on Natural Language processing and Chinese computing, NLPCC 2014

作者： Long, Wen-Xu Gao, Ji-xun Yu, Zheng-tao Gao, Sheng-xiang Hong, Xu-dong School of Information Engineering and Automation Kunming University of Science and Technology Kunming650051 China The Intelligent Information Processing Key Laboratory Kunming University of Science and Technology Kunming650051 China School of Computer Science Henan Institute of Engineering Zhengzhou451191 China

ISBN: (纸本)9783662459232

On account of the characteristics of online Chinese-Vietnamese topic detection, we propose a Chinese-Vietnamese bilingual topic model based on the Recurrent Chinese Restaurant Process and integrated with event elements. First, the event elements, including the characters, the place and the time, will be extracted from the new dynamic bilingual news texts. Then the word pairs are tagged and aligned from the bilingual news and comments. Both the event elements and the aligned words are integrated into RCRP algorithm to construct the proposed bilingual topic detection model. Finally, we use the model to determine if the new documents will be grouped into a new category or classified into the existing categories, as a result, to detect a topic. Through the contrast experiment, the proposed model achieves a good effect on topic detection. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Computers

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Twin Support Vector Machines Based on the Mixed Kernel Function

Twin Support Vector Machines Based on the Mixed Kernel Funct...

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The 6th International Conference on Computer Research and Development

作者： Fulin Wu Shifei Ding School of Computer Science and Technology China University of Mining and Technology Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

The efficiency and performance of the Twin Support Vector Machines(TWSVM) are better than the traditional support vector machines when it deals with the problems. However, it also has the problem of selecting kernel functions. Generally, TWSVM selects the Gaussian radial basis kernel function. Although it has a strong learning ability, its generalization ability is relatively weak. In a certain extent, this will limit the performance of TWSVM. In order to solve the problem of selecting kernel functions in TWSVM, we propose the twin support vector machines based on the mixed kernel function(MK-TWSVM) in this paper. To make full use of the learning ability of local kernel functions and the excellent generalization ability of global kernel functions, MK-TWSVM selects a global kernel function and a local kernel function to construct a mixed kernel function which has the better performance. The experimental results indicate that the mixed kernel function makes TWSVM have the good learning ability and generalization ability. So it improves the performance of TWSVM.

关键词： mixed kernel function TWSVM kernel function

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Cognitive Memory Systems In Consciousness And Memory Model

Cognitive Memory Systems In Consciousness And Memory Model

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International Joint Conference on Neural Networks

作者： Zhongzhi Shi Xiaofeng Wang Xi Yang Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences Beijing China Institute of Computing Technology Chinese Academy of Sciences Beijing China

Memory is a fundamental component in human brain and plays very important roles for all mental processes. The analysis of memory systems through cognitive architectures can be performed at the computational, or functional level, on the basis of empirical data. In this paper we discuss memory systems in the extended Consciousness and Memory Model (CAM) The knowledge representations used in CAM for working memory, semantic memory, episodic memory and procedural memory are introduced. It will be explained how, in CAM, all of these knowledge types are represented in dynamic decription logic (DDL), a formal logic with the capability for description and reasoning regarding dynamic application domains characterized by actions.

关键词： Semantics Computer aided manufacturing Trajectory Computational modeling Computer architecture Ontologies Cognition

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A secure broadcasting method based on the generalized aryabhata remainder theorem

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Journal of information Hiding and Multimedia Signal processing 2014年第4期5卷 709-718页

作者： Liu, Yanjun Chang, Chin-Chen Key Laboratory of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University No.111 Jiulong Rd Hefei230601 China Department of Computer Science and Information Engineering Asia University No.500 Lioufeng Rd Wufeng Taichung413 Taiwan Department of Information Engineering and Computer Science Feng Chia University No.100 Wenhwa Rd Seatwen Taichung407 Taiwan

With the prevalence of group communications, how to implement secure broadcasting among group members has become one of the most important issues. Broadcasting is a point-to-multipoint communication, and secure broadcasting should ensure that only authorized group members can obtain the correct content of the message that is broadcast by a sender. In this paper, we propose a secure broadcasting method based on the generalized Aryabhata remainder theorem (GART). By the use of the RSA public-key scheme, the proposed scheme allows the sender to send one copy of an encrypted message to all group members, but only the authorized members can recover the plaintext. Analysis showed that our scheme is secure and efficient. © 2014.

关键词： Cryptography

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Representative local features mining for large-scale near-duplicates retrieval

Representative local features mining for large-scale near-du...

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Xiaoguang Gu Yongdong Zhang Dongming Zhang Jintao Li Key Lab of Intelligent Information Processing of Chinese Academy of Sciences (CAS) Institute of Computing Technology CAS Beijing China

Local features have been widely used in many computer vision related researches, such as near-duplicate image and video retrieval. However, the storage and query cost of local features become prohibitive on large-scale database. In this paper, we propose a representative local features mining method to generate a compact but more effective feature subset. First, we do an unsupervised annotation for all similar images(or frames in video) in the database. Second, we compute a comprehensive score for every local feature. The score function combines the robustness and discrimination. Finally, we sort all the local features in an image by their scores and the low-score local features can be removed. The selected local features are robust and discriminative, which can guarantee the better retrieval quality than using full of the original feature set. By our method, the number of local features can be significantly reduced and a large amount of storage and computational cost can be saved. The experimental results show that we can use 30% of the features to get a better query performance than that of full feature set.

关键词： Databases Robustness Vectors Visualization Feature extraction Binary codes Complexity theory

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Forecasting wheat aphid with remote sensing based on relevance vector machine

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Nongye Gongcheng Xuebao/Transactions of the Chinese Society of Agricultural Engineering 2015年第6期31卷 201-207页

作者： Tang, Cuicui Huang, Wenjiang Luo, Juhua Liang, Dong Zhao, Jinling Huang, Linsheng Key Laboratory of Intelligent Computing & Signal Processing Ministry of Education Anhui University Hefei230039 China School of Electronic and Information Engineering Anhui University Hefei230039 China Key Laboratory of Digital Earth Science Institute of Remote Sensing and Digital Earth Chinese Academy of Sciences Beijing100094 China Nanjing Institute of Geography and Limnology Chinese Academy of Sciences Nanjing210008 China

The prevalence of aphid in winter wheat field has a significant impact on the production of winter wheat. An effective and timely forewarning of the scope and severity of the disease at a regional scale will not only reduce yield losses but also alert the stakeholders to take effective preventive measures. Forecasting aphid occurrence with Remote Sensing has great advantages over traditional methods and meteorological data, such as lower cost, simpler operation, more real-time and higher resolution. Chinese HJ-1A/1B data which have a high revisit frequency ( ©, 2015, Chinese Society of Agricultural Engineering. All right reserved.

关键词： Satellite imagery

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Availability-Aware Virtual Network Embedding for Multi-tier Applications in Cloud Networks

Availability-Aware Virtual Network Embedding for Multi-tier ...

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IEEE International Conference on High Performance computing and Communications (HPCC)

作者： Meng Shen Xu Ke Fuliang Li Fan Li Liehuang Zhu Lei Guan Ministry of Education Key Laboratory of Computer Network and Information Integration (Southeast University) P. R. China Beijing Engineering Research Center of High Volume Language Information Processing and Cloud Computing Applications School of Computer Science Beijing Institute of Technology P. R. China Tsinghua University Beijing Beijing CN College of Information Science and Engineering Northeastern University P. R. China DNSLAB China Internet Network Iniormation Center Beijing P. R. China School of Management & Economics Beijing Institute of Technology P. R. China

ISBN: (纸本)9781479989386

There is a growing trend for service providers (SPs) to migrate their multi-tier applications from local clusters to public cloud networks. In the cloud environment, it is a great concern of SPs to improve the availability of their virtual networks, in addition to guarantees of their virtual resource requirements, such as VMs and bandwidth. However, meeting these requirements results in an inefficient utilization of physical resources, which goes against the operational goal of cloud providers. To address this challenge, in this paper, we propose an availability-aware virtual network embedding framework that simultaneously improves the availability of virtual networks and the resource efficiency. We first propose a new metric to quantify the availability cost of a multi-tier virtual network, and then formulate the embedding problem as a joint optimization of the aggregated bandwidth and availability costs. Due to the NP-hardness of the embedding problem, we devise a heuristic algorithm that can solve the problem in polynomial time. Extensive simulation results show that the proposed algorithm enables CP to achieve various trade-offs between resource efficiency and availability, and to gain more revenue (e.g., 16.1% under a datacenter load of 80%) than the availability-agonistic algorithm.

关键词： Bandwidth Cloud computing Topology Network topology Servers Optimization Algorithm design and analysis

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