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2016 4th IEEE International Conference on Cloud computing and Intelligence Systems（IEEE CCIS2016）

作者： Chunshan Wu Yongqiang Weng Qiaowei Jiang Wenming Guo Cong Wang Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of Software Engineering Beijing University of Post and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education School of AutomationBeijing University of Post and Telecommunications

ISBN: (纸本)9781509012572

Data mining is a process of discovering information from large datasets by using automated algorithms, which makes it difficult for users to intuitively understand, explore and optimize the datasets and algorithms process. Recently with the development of the visual field, researchers have been exploring how to use the visualization methods to make users intuitively understand datasets and algorithms. In this paper we introduce the concept of visual data mining and dissect the visual data mining technology, mainly focusing on three related aspects: source data, data mining processes and data mining results;then design and implement a visual mining system based on decision tree algorithm, which achieves the encapsulation of data mining algorithms, and presents to the user a simple interactive interface, so that users can carry out visual data mining;finally apply the visual data mining technology to the survey data of elderly anxiety patients, and analyze the decision rules of anxiety disorders, which has important significance for clinical research and decision-making.

关键词： visualization data mining medical data analysis

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MapReduce-based efficient betweenness approximation pivot method for large graphs

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International Journal of Information Technology and Management 2016年第2期15卷 144-167页

作者： Deng, Xiao Long Li, Yu Xiao Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications 10 Xitucheng Road Beijing100876 China

The important person is vital for information spreading efficiency in social networks, which has always been the hottest research field in recent years. Nowadays, with the increased information spreading speed in our daily life such as cellphone or microblog, the government and enterprise have realised that it is necessary and important to manage and control the information spreading in social networks of people by recognising the important person or VIP customer. Meanwhile, with the rapid increase of information in society activities recently, the distributed information system engineering such as MapReduce-based computation system has become more and more popular in large-scale social network data analysis in emergency case management or VIP customer recognition. In this article, a novel effective and efficient node betweenness approximation pivot selection method for largescale graphs is proposed based on MapReduce-based system for social network analysis (SNA). Furthermore, it has been proved useful in four discrete datasets and one continuous dataset (six month cellphone call graph) in VIP customer discovery for large graphs from real telecom data in China to help deal with customer relationship management more efficiently. Copyright © 2016 Inderscience Enterprises Ltd.

关键词： MapReduce

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Secure transmission with artificial noise in heterogeneous massive MIMO network 1st

Secure transmission with artificial noise in heterogeneous m...

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1st International Congress on Signal and Information Processing, Networking and Computers, ICSINC 2015

作者： Li, Chang Sun, Songlin Liu, Wei Huang, Hai School of Information and Communication Engineering Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China Department of Network and Platform M2M & Internet of Things Institute China Mobile Research Institute Beijing China

ISBN: (纸本)9781138028814

Heterogeneous Network (HetNet) is a promising technology to improve the capacity of future generations of cellular network, in which a mobile station can be served by multiple Base Stations (BSs) with different scales of coverage range, including short range Low Power Nodes (LPNs). In this paper, we study security provisioning in heterogeneous massive Multiple-Input–Multiple-Output (MIMO) systems. Specifically, we consider secure downlink transmission in a massive MIMO system with Matched-Filter (MF) precoding and Artificial Noise (AN) generation at the BS, and transmit the signal to the MT through the LPN in the presence of a passive multi-antenna eavesdropper. Thereby, we consider an AN shaping matrix, where the AN is transmitted in the null-space of the matrix formed by all MT channels. Our analytical and numerical results reveal that, in massive MIMO systems employing MF precoding and AN generation, the Signal-to- Interference-and Noise Ratio (SINR) of intended MTs in LPNs is higher than eavesdropper, we can also obtain the positive secrecy capacity which prove this method can guarantee the secure transmission. © 2016 Taylor & Francis Group, London.

关键词： Heterogeneous networks

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Community-Based Recommendations: A Solution to the Vulnerability Problem

Community-Based Recommendations: A Solution to the Vulnerabi...

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International Conference on Semantics, Knowledge and Grid (SKG)

作者： Jiali Dong Xiaoyong Li Binxing Fang Beijing University of Post and Telecommunications BUPT Beijing China Ministry of Education BUPT Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Beijing China

ISBN: (纸本)9781509047963

Recommender systems assist users in the daunting task of sifting through large amounts of data in order to select relevant information or items. Unfortunately, such systems may be subject to attack by malicious users who want to manipulate the system's recommendations to suit their needs: to promote their own (or demote a competitor's) product/service, or to cause disruption in the recommender system. Attacks can cause the recommender system to become unreliable and untrustworthy, resulting in user dissatisfaction. In this paper, we proposed a community-based recommendation system. The presented approach the rating matrix to extract preferences for each user, and detect communities according to user preferences similarity. The predicted rating is calculated by user in the same community, and malicious users will be in one community for the similar behavior, therefore recommendation systems can reduce the impact of malicious users. Experimental results show that the community-based recommendations is more robust than traditional systems.

关键词： Prediction algorithms Robustness Recommender systems Matrix decomposition Collaboration Companies Motion pictures

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TEXT SUMMARIZATION USING SENTENCE-LEVEL SEMANTIC GRAPH MODEL

TEXT SUMMARIZATION USING SENTENCE-LEVEL SEMANTIC GRAPH MODEL

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2016 4th IEEE International Conference on Cloud computing and Intelligence Systems（IEEE CCIS2016）

作者： Xu Han Tao Lv Qiaowei Jiang Xinyan Wang Cong Wang School of Software Engineering Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Air Force General Hospital

ISBN: (纸本)9781509012572

Text summarization is to generate a condensed version of the original document. The major issues for text summarization are eliminating redundant information,identifying important difference among documents and covering the informative content. In this paper, we propose a Sentence-Level Semantic Graph Model（SLSGM） which exploits the semantic information of sentence. SLSGM considers sentences as vertexes while the semantic relationship between sentences as the *** calculate the relevance values between sentences using semantic analysis and take the values as weights of edges while sentences’ values are scored by a variant of the traditional Page Rank graph ranking algorithm considering both internal and external information. The experimental results show that the applicability of the model to text summarization is feasible and effective.

关键词： Graph-based model Text summarization Semantic analysis

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An Optimal Controller Design for CPS with Stochastic Time Delay

An Optimal Controller Design for CPS with Stochastic Time De...

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International Conference on Mobile Ad-hoc and Sensor Networks, MSN

作者： Leilei Lou Xu Zhang Dongbin Wang School of Network Education Beijing University of Posts and Telecommunications Beijing China Ministry of Education Beijing Key Laboratory of Trustworthy Distributed Computing and Service(BUPT) Beijing China

ISBN: (纸本)9781509056972

Since Cyber-Physical System (CPS) is defined as integrations of computation, communication and control to physical processes, the communication plays an important role in such system. Compared with the traditional control system, the control in CPS is very difficult because the communication networks inevitably introduce variable time delays and possible lost of samples. In Networked Control System (NCS), there are some related works to discuss the problem of time delay. However it still needs to evaluate and improve those existing schemes in CPS. In this paper, a novel dynamic timeout scheme and actuator compensation by using a hidden Markov model for the time delay to reduce the influence of random time delays has been proposed. Simulation results on TrueTime 2.0 demonstrate the feasibility and effectiveness of this networked real-time control strategy.

关键词： Delay effects Hidden Markov models Delays Actuators Markov processes

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r-RADAR: Obtain the maximum throughput when an energy harvesting relay node is applied in multiuser OFDMA networks

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Journal of Communications 2016年第11期11卷 957-969页

作者： Xue, Liang Liu, Ying Wang, Yanlong Li, Zuopeng Fan, Yongjian School of Information and Electrical Engineering Hebei University of Engineering Handan056038 China Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications Ministry of Education Beijing100876 China

The joint resource allocation for multiuser Orthogonal Frequency Division Multiple Access (OFDMA) relay networks is studied in the paper, where the relay node has renewable energy supplies and can be driven by energy collected from Radio Frequency (RF) signals from the source node. The relay node with green energy supplies uses Power Splitting (PS) scheme for Simultaneous of Wireless Information and Power Transfer (SWIPT). The joint resource allocation problem is formulated to maximize the throughput under several constraints including subcarrier pairing, power splitting ratio, power allocation, and subcarrier pairing allocation while satisfying data rate requirements for multiuser OFDMA relay networks. Due to the specialized problem is non-convex and difficult to be solved in finite polynomial time, a reconfigurable resource allocation by using the decoupling approach in a framework of repetitive (r-RADAR) algorithm with low computational complexity is proposed in the paper, which takes advantage of the unique problem structure and reduce the domain of search space. The global optimality is theoretically proven and well obtained when we using r-RADAR algorithm. Simulation results further validate the better performances of our proposed r-RADAR algorithm when it is compared to the other two related benchmark algorithms. © 2016 Journal of Communications.

关键词： Energy harvesting

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A User-Centric Approach to Activity Recognition and Guidance in Semantic Smart Home

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China Communications 2015年第S2期12卷 103-113页

作者： LI Haitao GUO Kun LU Yueming LI Yonghua South China University of Technology Guangdong Power Grid Co. Ltd Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education

Wireless smart home system is to facilitate people's lives and it trend to adopt a more intelligent way to provide services. It is very desirable in the recent SH market for the system to recognize users' behaviors and automatically response the corresponding activities to satisfy users' actual demands. However, activity models in the existing approaches are usually defined separately through knowledge-driven methods. These approaches cause that the activity models can't be matched with the services dynamically. To address the problem, we develop the semantic association model and a novel approach of activity recognition and guidance is presented. In our approach, the smart devices and users' requirements are described by semantic models. When the requirements are detected and understood, smart gateway can provide appropriate services, achieving activity assistance. The semantic association model allows all related elements in smart home connect with each other logically. The approach has been implemented and the results show that the success rate of the approach based on semantic association model is higher than 33% at average as compared to the approach based on predefined models. The proposed approach can effectively help people who are in trouble with learning or remembering in the common life.

关键词： Internet of Things smart home activity recognition activity guidance semantic model

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Throughput performance improvement in cognitive radio networks based on spectrum prediction

Throughput performance improvement in cognitive radio networ...

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International Symposium on Communications and Information Technologies (ISCIT)

作者： Fukang Hou Xin Chen Hai Huang Xiaojun Jing Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education Beijing University of Posts and Telecommunications School of Information and Communication Engineering Beijing University of Posts and Telecommunications China

ISBN: (纸本)9781509041008

Spectrum sensing is used to detect spectrum holes and find active primary users while randomly selecting channel for sensing leads to secondary user's low throughput in cognitive radio networks. Spectrum prediction forecasts future channel status on the basis of historical information, and BP neural network is used as an example of the prediction method. Second users' frame structure is redesigned in this paper based on spectrum prediction, aiming to select the most likely idle channel for sensing. Theoretical and simulation results show that secondary users' throughputs are significantly improved by spectrum prediction. Correlations both in the frequency domain and time domain are compared, and the impacts of the prediction method, traffic intensity, and channel number on the throughput are also investigated in this study.

关键词： time-domain analysis backpropagation cognitive radio frequency-domain analysis signal detection Cognitive radio Frequency-domain analysis Time domain analysis back propagation signal acquisition Throughput Spectra channel status Channel numbers BP neural networks Consumers Radio networks

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AN IMPROVED TEXT SIMILARITY ALGORITHM RESEARCH FOR CLINICAL DECISION SUPPORT SYSTEM

AN IMPROVED TEXT SIMILARITY ALGORITHM RESEARCH FOR CLINICAL ...

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2016 4th IEEE International Conference on Cloud computing and Intelligence Systems（IEEE CCIS2016）

作者： Wen Wang Qiaowei Jiang Tao Lv Wenming Guo Cong Wang School of Automation Beijing University of Posts and Telecommunications Key Laboratory of Trustworthy Distributed Computing and Service Beijing University of Posts and Telecommunications School of Software Engineering Beijing University of Posts and Telecommunications

ISBN: (纸本)9781509012572

The paper presents an improved text similarity algorithm and applies to the Clinical Decision Support System. It can improve the efficiency of decision making. After analyzing the disadvantages of the conventional TF-IDF algorithm and Cosine Similarity calculation, we propose an improvement to the text similarity algorithm. The proposed algorithm takes into full consideration the impact of semantically-similar keywords and textually-similar keywords on text similarity, therefore achieves improved accuracy. The function of this Clinical Decision Support System is to search for relevant biomedical articles and locate solutions.

关键词： Vector Space Model Text Similarity Semantic Analysis Words Coverage

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