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International Conference on Cyberspace Technology, CCT 2014

作者： Ma, Jing Lu, Yueming School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service BUPT Ministry of Education Beijing China

ISBN: (纸本)9781849199285

In a large-scale network environment, the Internet has produced an amount of digital information such as social media, e-commercial comments, online shopping records and advertising click logs. So, recommend systems not only furnish users with satisfied requirements but also bring about healthy profit to companies. To cope with massive data, we proposed an effective recommend system (ERS) for modelling abundant history data. Firstly, we advise a new data split strategy to make the recommend system fit for large scale advertising. Then, a distributed-recommendation algorithm is designed. Finally, we apply ERS and distributed computing and storage tools (such as Spark, Hadoop, etc.) to model history data aiming at improving the system efficiency. In this paper, we also compare and analyse diverse performances of ERS including its efficiency and its accuracy.

关键词： Metadata

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A tensor-based sub-mode coordinate algorithm for stock prediction 3

A tensor-based sub-mode coordinate algorithm for stock predi...

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3rd IEEE International Conference on Data Science in Cyberspace, DSC 2018

作者： Huang, Jieyun Zhang, Yunjia Zhang, Jialai Zhang, Xi Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing China School of Electronic Information Sichuan University Chengdu China

ISBN: (纸本)9781538642108

The investment on the stock market is prone to be affected by the Internet. For the purpose of improving the prediction accuracy, we propose a multi-task stock prediction model that not only considers the stock correlations but also supports multi-source data fusion. Our proposed model first utilizes tensor to integrate the multi-sourced data, including financial Web news, investors' sentiments extracted from the social network and some quantitative data on stocks. In this way, the intrinsic relationships among different information sources can be captured, and meanwhile, multi-sourced information can be complemented to solve the data sparsity problem. Secondly, we propose an improved sub-mode coordinate algorithm (SMC). SMC is based on the stock similarity, aiming to reduce the variance of their subspace in each dimension produced by the tensor decomposition. The algorithm is able to improve the quality of the input features, and thus improves the prediction accuracy. And the paper utilizes the Long Short-Term Memory (LSTM) neural network model to predict the stock fluctuation trends. Finally, the experiments on 78 A-share stocks in CSI 100 and thirteen popular HK stocks in the year 2015 and 2016 are conducted. The results demonstrate the improvement on the prediction accuracy and the effectiveness of the proposed model. © 2018 IEEE.

关键词： Tensors

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A method based on MD5 and time for preventing deception in electronic commerce

A method based on MD5 and time for preventing deception in e...

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International Conference on Cyberspace Technology, CCT 2014

作者： Hu, Zhenggang Lu, Yueming School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China Key Laboratory of Trustworthy Distributed Computing and Service BUPT Ministry of Education Beijing China

ISBN: (纸本)9781849199285

Aiming at reducing the risk of data being intercepted and preventing deceptions in the electronic commerce, this paper proposes a method based on MD5 and time which can effectively prevent the deception in data transmission. The method uses the traditional MD5 algorithm to encrypt and validate important data, then verifying the validity and legitimacy of the data by using time.

关键词： Electronic commerce MD5 algorithm Preventing deception Time

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Chinese Open Relation Extraction with Pointer-Generator Networks

Chinese Open Relation Extraction with Pointer-Generator Netw...

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Ziheng Cheng Xu Wu Xiaqing Xie Jingchen Wu Ministry of Education Key Laboratory of Trustworthy Distributed Computing and Service

ISBN: (数字)9781728195582

ISBN: (纸本)9781728195599

Most of the traditional Chinese open relation extraction (Open RE) system exploit the syntactic, lexical and other language structure information obtained by natural language processing (NLP) tools from sentences to build hand-crafted patterns for extraction, which is easy to cause error propagation and affect the accuracy of extraction. In this paper, we propose an end-to-end abstract Chinese Open RE model based on the Pointer-Generator network, PGCORE. We employ the results extracted by the state-of-the-art pattern-based Chinese Open RE system as the training set of the model. Experimental results show that our method is outperforms the pattern-based several baselines system, which proves the feasibility and effectiveness of using deep learning models for Chinese Open RE.

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Real-time Event Detection and Tracking in Microblog via Text Chain and Sentiment time series

Real-time Event Detection and Tracking in Microblog via Text...

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IEEE International Conference on Data Science in Cyberspace (DSC)

作者： Bingxu Piao Xu Wu Jingchen Wu Xiaqing Xie Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education

ISBN: (数字)9781728195582

ISBN: (纸本)9781728195599

Microblog becomes one of the most popular media for sharing first-hand information. As more close to real event, detecting and tracking event in microblogs is a research hotspot. To alleviate feature sparsity problem, traditional event detection and tracking methods exploit comments, replies, and reposts to enrich the information of posts. However, ignoring text relationship only leads to more irrelevant information. Aiming at this issue, a novel real-time event detection and tracking method for microblog stream is proposed. For each microblog from the real-time stream, similarity against historical event set is first evaluated. Then, known event microblogs are partitioned by the proposed method sentiment time series, clustered based on word relation graph, and compare with the previous graph to track burst keywords. Meanwhile, text chain is introduced to detect events for unknown event microblogs. Text chain is a unique relationship of microblogs, in which comments, replies, and reposts are used to form a word relation graph of the corresponding post. Posts and attached graphs are clustered to detect new events. Experiments are performed on real-time microblog datasets to evaluate the effectiveness of methods. Results show that the proposed method gains better F-measure than similar methods.

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Multiple Vandermonde Decomposition Based Channel Estimation for Mm Wave MIMO High-Mobility Communication in 5G and Beyond

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China Communications 2023年第4期20卷 12-25页

作者： Zhao Yi Xiaojun Jing School of Electronics and Information Hunan First Normal UniversityChangsha 410205China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of EducationBeijing University of Posts and TelecommunicationsBeijing 100876China School of Information and Communication Engineering Beijing University of Posts and TelecommunicationsBeijing 100876China

Millimeter wave(mmWave)massive massive multiple input multiple output(MIMO)technique has been regarded as the viable solution for vehicular communications in 5G and *** achieve the substantial increase in date rates,it is important to take an effective channel state information(CSI).However,existing channel estimation strategies are unavailable since the users *** solve above issues,in this paper,inspired by a specific antenna structure,we propose a novel approach for fast time-varying channel ***,by considering the vehicle scenario with high-mobility,a corresponding mathematical model is firstly ***,based on the special structural of the sparse array,the switch network is used to replace the convention phase shifter of mmWave hybrid system,which can effectively reduce the number of radio-frequency(RF)chains and ***,by solving the semidefinite programming(SDP)duality problem,the Doppler frequency and path parameters are effectively *** results are shown that the computational complexity and estimation accuracy of the proposed algorithm is superior than that of the traditional schemes.

关键词： MIMO mmWave channel estimation high-mobility time-variant

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Neural Network Based Target User Recognition Model for Network Community 6

Neural Network Based Target User Recognition Model for Netwo...

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6th Annual 2018 International Conference on Geo-Spatial Knowledge and Intelligence, GSKI 2018

作者： Wu, Xu Dai, Yulun Xie, Xiaqing Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education China School of Cyberspace Security BUPT China Beijing University of Posts and Telecommunications Library Beijing100876 China

For multi-dimensional feature of user data in network community, available methods mainly use Rank scoring algorithm or user classification algorithm for target user recognition. However, Rank method has a low performance, and the classification algorithm needs high construction cost. Therefore, this paper uses a target user recognition model integrating the user content analysis and the user behavior analysis to improve performance and speed of the target user recognition by a neural network content analysis model with a single-layer neural network and N-gram features for discovering automatically the user feature. The proposed method outperforms the current Rank scoring and classification methods in terms of performance, in which the F value reaches 0.89 and the accuracy reaches 0.91. Moreover, avoiding the cost of manual design dependent on specific tasks shortens the training time. Ten thousand data can be modeled in one minute. © Published under licence by IOP Publishing Ltd.

关键词： Network layers

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Construction and implementation of 'classic reading' innovation platform

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Journal of China Universities of Posts and Telecommunications 2013年第SUPPL -2期20卷 128-135页

作者： Wu, Xu Xu, Jin Xie, Xia-Qing Gao, Xue-Bin School of Computer Science Beijing University of Posts and Telecommunications Beijing 100876 China Key Laboratory of Trustworthy Distributed Computing and Service Ministry of Education Beijing University of Posts and Telecommunications Beijing 100876 China Beijing University of Posts and Telecommunications Library Beijing 100876 China

In order to effectively promote classic reading and guide students to read classics recommended by scholars, this paper constructs an innovation platform of 'Classic Reading' teaching system based on reading credit. According to the requirements of innovation, teaching reformation and actual needs of students, this innovation platform designs five modules, including user security-login module, book management module, reading-report module, system management module and teaching activities module. For the online part, this platform implements the 'Happy Reading' network teaching platform, including user security-login through electronic identity (eID), visualization of book information, online writing, submission, reviewing, publishing and socializing comments of reading-report, statistical analysis and other practical functions. Offline, the platform continuously optimizes book list to ensure the quality of classic reading, and sets reviewing standards to ensure the quality of reading-reports. In the meanwhile, with the help of students' organizations, the platform carries out activities like 'Readers Sloan', 'Reading Star' and many other colorful activities. The combination of online and offline parts provides a reliable, convenient, interactive and efficient teaching system. It has been proved that this platform has significantly improved teaching quality and efficiency, and enhanced students' comprehensive quality, especially for students in science and engineering colleges. © 2013 The Journal of China Universities of Posts and Telecommunications.

关键词： Students

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Dynamic Music emotion recognition based on CNN-BiLSTM

Dynamic Music emotion recognition based on CNN-BiLSTM

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IEEE Information Technology and Mechatronics Engineering Conference (ITOEC)

作者： Pengfei Du Xiaoyong Li Yali Gao Key Laboratory of Trustworthy Distributed Computing and Service (BUPT) Ministry of Education

ISBN: (数字)9781728143231

ISBN: (纸本)9781728143248

Most of the music information will express the emotional signal, the emotional classification of music can be more convenient for the organization and retrieval of music, is the use of music for psychological intervention and physiological adjustment of the premise. In this paper, the dynamic emotion recognition of music, using the VA model, a song to produce a set of VA value. This paper first elaborates the relevant background and emotion classification model of music emotion recognition, and explain the representations of emotion, designs the overall framework of dynamic music emotion recognition, and adopts the convolution neural network and the BiLSTM fusion way to carry on the music dynamic VA And then compared with other relevant methods of identification.

关键词： Music Emotion recognition Feature extraction Logic gates Multiple signal classification Psychology Task analysis

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A multi feature fusion clustering algorithm based on q&a community

A multi feature fusion clustering algorithm based on q&a com...

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International Conference on Cyberspace Technology, CCT 2013

作者： Qian, Diandian Li, Yonghua Lu, Yueming Key Laboratary of Trustworthy Distributed Computing and Service Ministry of Education School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing 100876 China

ISBN: (纸本)9781849198011

In this paper, a multi feature fusion clustering algorithm based on the Q&A community is presented, which to extract the candidate label by performing clustering on the Q-A pairs. It is proposed to combine TF/IDF, context information entropy, word length as feature to extract, select and score keywords. The experiment not only confirms effectiveness the compared with the traditional system, but also validates the precision of the multi feature fusion model.

关键词： Clustering Feature Fusion Q&A community. TF/IDF

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