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    21 August 2015, Volume 31 Issue 7
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    Big Data Technology:Current Applications and Prospects
    Jianxin Liao
    2015, 31(7):  1-12.  doi:10.11959/j.issn.1000-0801.2015189
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    The research includes computer science,information science,management science,psychology,etc.Four key technologies in big data research,data collection,preprocessing and storage,data analysis and mining,data privacy protection,data center system structure were discussed and the hot research topics from domestic and overseas research groups were demonstrated in order to have comprehensive and systematic understanding of big data.The application status of big data was introduced from three perspectives,application platforms,relevant products and standardization.Meanwhile,description of current business in big data and other field was presented.Eventually,the opportunities and challenges in big data research were revealed through big data analysis strategies,privacy protection and data quality,which provide the guideline for future research.

    viewpoint
    Data-Driven Retention Marketing Development Strategy in Telecom Enterprise
    Chenxi Qi,Yiming Yu
    2015, 31(7):  13-17.  doi:10.11959/j.issn.1000-0801.2015175
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    As the new market shrink,some new product market become even to zero,the marketing strategy goal transfer from acquisition to customer retention in the telecom enterprise.Because of the gap between the retention marketing goal and the marketing reality,it was discussed how the telecom company could develop data-driven marketing of retention.Firstly,design the ability architecture of data-driven retention marketing IT system.Secondly,distinct and establish the management and operational process of retention marketing.Thirdly,establish the two foundation databases,one is the customer needs’ labels database,and the other is marketing and campaign resources database.Fourthly,improve and establish the three kinds of core abilities-including the ability of allocation of marketing resource for the customer needs,the ability of the channel triggering and the ability of the visual management of retention marketing.

    Cloud-Based Big Data Technology
    Feng Wang,Mingchuan Yang,Yuan Liu,Heyu Wang
    2015, 31(7):  18-23.  doi:10.11959/j.issn.1000-0801.2015168
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    The development direction of big data technology was analyzed.The necessity and feasibility for integrating cloud computing and big data were discussed.Then,typical case studies of current mainstream technology were present,and the most critical problems and corresponding solutions for future development of cloud-based big data technology were concluded.

    Reflection on Network Element Evolution of Big Data Management for Telecom Operators
    Jun Zhao,Yirong Shi
    2015, 31(7):  24-28.  doi:10.11959/j.issn.1000-0801.2015167
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    Big data has had a profound impact on the future of telecommunications operators,and perhaps even subversive type business model change.The present situation of the application of big data and existing problems of telecom operators were analyzed,and the centralized and decentralized big data service models were compared.The big data network element architecture based on scattered data and implementation of the recommendations were proposed.

    Operation Management Mode Based on New Media Technology
    Peng Han
    2015, 31(7):  29-33.  doi:10.11959/j.issn.1000-0801.2015172
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    For tremendous impact has brought by the rapid development of the new media(such as Weibo,We-chat,micro video,e.g.)and the mobile internet,the difficulties the operators faced in the new media field and the way to deal with the challenges were analyzed.The methods and procedures for the new media analysis technique were proposed.The application of the new media technology in the marketing support analysis in several cases was elaborated.The function implementation of operational management and complaint management from the perspective of operational management were introduced,and then the system construction scheme and implementation effect for the new media operation and management system development were presented.

    research and development
    Analysis and Semantic Mining in Heterogeneous Information Network
    Rui Wang,Zhiqiang Zhang,Chuan Shi
    2015, 31(7):  43-51.  doi:10.11959/j.issn.1000-0801.2015166
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    Heterogeneous information network(HIN),which is composed of different types of objects and links,has gradually become a hot topic in social network analysis.As a unique characteristic of HIN,meta path contains rich semantic information.Heterogeneous information network with values on links are ubiquitous in real world.Therefore,the traditional meta path,which doesn’t consider weight on links,can not exactly capture semantics in many cases.Related concepts of HIN were introduced and a brief introduction of applications of HIN was given.Then subtle semantic information in HIN was explored by extending the traditional meta path to weighted meta path.Experiments on two real data sets demonstrate the applications of the weighted meta path in recommendation,relevance search.

    An AkNN Algorithm for High-Dimensional Big Data
    Zhongwei Wang,Yefang Chen,Siyou Xiao,Jiangbo Qian
    2015, 31(7):  52-62.  doi:10.11959/j.issn.1000-0801.2015171
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    A new variant of k nearest neighbor queries,which called as all k-nearest neighbor queries(AkNN),is a process to search the k nearest neighbors of each object in a data set.An AkNN query algorithm for high-dimensional big data on the Hadoop system was proposed.Using the banding technique and the p-stable LSH algorithm,dimensionality reduction was performed,then the data was embeded in a Z-order curve.The preprocessed data were continued to be treated on a MapReduce framework in a distributed parallel manner.Experimental results show that the proposed algorithm can efficiently handle AkNN queries for large-scale high-dimensional data.

    An Adaptive Subspace Similarity Search Approach
    Jianxin Ren,Huahui Chen
    2015, 31(7):  63-74.  doi:10.11959/j.issn.1000-0801.2015190
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    In recent years,such database fields as multimedia information retrieval,similarity join and time series matching,where similarity search has attracted much attention.Existing researches mostly compute nearest neighbor to solve problems about search target set,such as kNN and kNNJ,by metric distance functions in the Euclidean space.But some studies showed that high dissimilarity dimensions had got great effect on the accuracy of answer and flexibility and robustness still were lacked in corresponding solutions.Thus centralized dynamic subspace or partial dimensions similarity search problem and algorithms were proposed at first.Furthermore,with the emerge of very large dataset,centralized algorithms can,t extend very well.Finally,the distributed ones under hadoop framework were proposed.Experiments prove that distributed algorithms outperform centralized ones in the performance without accuracy loss.

    Cross-Domain Recommendation Algorithm Based on Latent Factor Model
    Sheng Gao,Siting Ren,Jun Guo
    2015, 31(7):  75-79.  doi:10.11959/j.issn.1000-0801.2015188
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    In the internet environment,the combining of multi-source heterogeneous information objects in different areas makes users face information selection dilemma problem in big data environment.It has been very difficulty for traditional information recommendation algorithms to adapt to the interdisciplinary information recommendation service.The evaluation model from a user clustering set to an information object clustering set has common characteristics of cross-domain and personality characteristics of single domain.By analyzing the evaluation data from users to information objects in different areas,these characteristics were extracted based on latent factor model.Then by transmitting and sharing the common characteristics of cross-domain,the data sparseness problem of target field was alleviated,which could improve the accuracy of cross-domain information recommendation.

    A Classification Method of Music Style Based on Text Mining and Neural Network
    Jianfeng Zhang,Jin Wang
    2015, 31(7):  79-85.  doi:10.11959/j.issn.1000-0801.2015179
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    In terms of the confusion of music style ambiguous relationships caused by artificial classification and the problem that some songs cannot be classified into the proper style,the emotion of songs based on their lyrics to classify their belongings was analyzed.BP neural network was used to establish a music style forecast model and then a reasonable proof of the theory and derivation was made.This experiment use MATLAB as a modeling tool and determine the training parameters according to its characteristics,and then extract 10% from dataset to test.This approach shows that theoretical results and data simulation results agree well with the accuracy rate reached about 80%.

    Collaborating Filtering Method Based on Multiple Data Sources
    Fushun Ke,Xiaohui Yao
    2015, 31(7):  86-89.  doi:10.11959/j.issn.1000-0801.2015164
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    The highly efficient utilization of multiple data sources is a key challenge in big data applications.Based on the collaborative filtering recommendation,services pick consumption behaviors of similar clients by clustering to generate the recommendation list.Client clustering contains two units,one is preliminary clustering,and the other is synthetic clustering.Preliminary clustering use client-product score matrixes,telecommunication service identities,client network behaviors and etc.to calculate similarities.Synthetic clustering weights the abundance of data,and then completes the similarity calculation and client clustering.Adjustable weights of data validity were introduced to optimize the system on the basis of click rates and conversion rates of recommendation list.

    Wide operating technology
    Research on Database Deployment Technology in Cloud Computing Environment
    Yongshun Cai,Mingchuan Yang,Wei Si,Shaoyang Rao
    2015, 31(7):  90-95.  doi:10.11959/j.issn.1000-0801.2015173
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    Cloud computing virtualization technology has the characteristics of elastic scalability,automatic migration (high availability),automatic recovery (high stability).Because of the natural complexity of database systems,it makes a big challenge to deploy database systems in cloud computing virtualization environment.On the basis of research and analyzing models of deploying database systems in private cloud environment,the TPC-C benchmark test with database instances running in cloud computing virtual machines was applied.Compared with performance results of same test with database instances running in physical machines,the feasibility of deploying database systems in cloud computing virtualization environment was verified.

    Research and Practice on Network Auto-Deployment of Cloud Resource Pool
    Peiyuan Lai,Weimin Ma,Yi Liu,Tian Chen
    2015, 31(7):  96-103.  doi:10.11959/j.issn.1000-0801.2015185
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    With the increasingly growth of cloud based resource pool,the network has become a bottleneck of the rapid service delivery.And the network automatic configuration technology has also become a new research topic as the requirement for inter service communication and migration across data centers becomes more imminent.The concept and applications scenarios of automatic network deployment based on server virtualization technology were described,and the key architecture and technology of software defined network were analyzed.Also the solution and practice of overly SDN technology were summarized,and an operational network architecture was proposed.Suggestion for multi-service provision and multi-tenant network of cloud resource pool automatic deployment was given.

    Approach and Practice of Illegal Voice Call Governance
    Hongyi Zhu,Jianhong Lin,Yanqing Wang,Jinran Zhang,Jingyu Wang
    2015, 31(7):  104-112.  doi:10.11959/j.issn.1000-0801.2015187
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    Telecom operators have been committed to the research of illegal voice call governance approach,which includes analyzing the risk origin,determining the management focus and formulating the prevention strategy.Through the establishment of big data analysis platform based on all kinds of call signaling collection,the call features of all kinds of illegal voice call were researched,the control system of illegal voice call(especially fraud call)was constructed,an all-around control was implemented,and the effect was obvious when the system was applied actually.

    Industrial Application Incubation Platform Based on PaaS Model of Cloud Computing
    Gang Lu,Boqing Liang,Xinzhang Yang,Zhenwei He
    2015, 31(7):  113-118.  doi:10.11959/j.issn.1000-0801.2015184
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    The combination of cloud computing and industrial applications is the key point of “internet +”,the mode of platform as a service can effectively reduce the costs of development and construction for industrial application,so that an effective innovation mechanism could be set up.The status and problems of industrial application incubation platform were introduced.By designing the service function and business model of the platform,the architecture based on PaaS technology was put forward.The key technologies involved such as container and mobile App development were analyzed.At last the development of the platform was prospected.

    Research and Design of Distributed Parallel Processing Cloud CTI System Architecture
    Qing Li,Wenhong Zhou
    2015, 31(7):  119-124.  doi:10.11959/j.issn.1000-0801.2015177
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    CTI is responsible for the agent registration management,scheduling management in call center.Therefore,the CTI system’s stability and performance of the integrated call center platform,the scale of the robustness of the agents will have a direct impact.Based on the research of distributed computing,a high reliability,parallel processing of call center cloud CTI system architecture was provided,as well as the dynamic of the system in the call center agent resources and scheduling need matching method,in order to improve the running stability of the large-scale,the ultra large scale call center platform flat core network element CTI system and the convenient of platform smooth expansion.

    Cloud Backup Solution
    Wei Si,Feng Wang
    2015, 31(7):  125-131.  doi:10.11959/j.issn.1000-0801.2015170
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    As a new data backup form,cloud backup service provides users with putting the local data backup to the remote cloud.The cloud backup is being more and more focused by the industry.Combined with the demand of data backup under cloud computing environment,three aspects of“end-pipe-cloud”cloud backup solution were comprehensively analyzed,including cloud backup client,cloud backup network channel and cloud backup resource pool.In addition,according to the different business scenarios and user demand,feasible public cloud and hybrid cloud backup solutions were proposed,which could provide an important reference for the research and deployment of related field.

    OpenStack-Based Heterogeneous Hybrid Cloud Solution
    Tian Chen,Nan Chen,Zhilan Huang,Yongbing Fan,Peiyuan Lai
    2015, 31(7):  132-138.  doi:10.11959/j.issn.1000-0801.2015169
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    The status of hybrid cloud industry,mainstream products and solutions of hybrid cloud were studied.The applicable scenaries and deployment options were analyzed.Based on the characteristics of cloud resource and the hybrid cloud business needs of telecom operators,heterogeneous hybrid cloud system and technical solutions were proposed.The system framework and key technologies of hybrid cloud unified management,heterogeneous resource pools unified management,hybrid cloud network connectivity,and hybrid cloud security were described.

    Big Data Application in Network Security Analysis
    Shuai Wang,Laifu Wang,Huamin Jin,Jun Shen
    2015, 31(7):  139-144.  doi:10.11959/j.issn.1000-0801.2015176
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    With the rapid growth of network security information scale,how to apply big data in network security analysis has become the network security research hotspot.From the perspective of the requirement of network security analysis and insufficient of traditional technique,the necessity of introducing big data analysis technology was analyzed,and the application of big data in network security analysis was discussed from aspects of security data storage,retrieval and analysis.On this basis,the network security analysis platform based on big data was proposed,and the correlation analysis methods of typical attack scenarios were detailed.

    Method of Building Signaling Big Data Real-Time Query Platform Based on Hadoop
    2015, 31(7):  145-151.  doi:10.11959/j.issn.1000-0801.2015186
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    With the popularity of 4G communication technology,and development of mobile internet application,the data flow is booming,and traditional processing method is difficult to support the massive signalling data real-time query requirement.Therefore,a kind of data real-time query platform based on Hadoop was put forward,to support the details of a single large scale signaling processing.Through data collection,data modeling,rowkey design,data compression and storage,etc.,real-time data query service was provided.Finally,the experimental environment of the current network was verified,which could get very good income.

    Comparison of Open-Source Distributed Computing Framework for Big Data
    Ai Fang,Xiong Xu,Bing Liang,Yuzhong Zhang,Yiping Yang
    2015, 31(7):  152-157.  doi:10.11959/j.issn.1000-0801.2015174
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    A comparison of three open source distributed computing frameworks for big data (Hive,Impala and Spark)was conducted.Tests were run to evaluate the performance aiming at real business demands.The cost of implementation to meet business requirements was also discussed.

    Research on Big Data Application for Security
    Deli Yang,Tao Zhang
    2015, 31(7):  164-168.  doi:10.11959/j.issn.1000-0801.2015178
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    Several data sources of big data on security were described,a closer look was taken at the implementation of big data platform on security,the main points and steps during the implementation were also proposed.Specially,detail analysis on the overall architecture and system structure of the big data platform on security were provided,the relationship with the existing video surveillance platform was also described.The implementation of big data platform on security must be promoted on the scale of data characteristics and algorithm maturity.

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Authorized by: China Association for Science and Technology
Sponsored by: China Institute of Communications
Posts and Telecom Press Co., Ltd.
Publisher: Beijing Xintong Media Co., Ltd.
Editor-in-Chief: Chen Shanzhi
Editorial Director: Li Caishan
Address: F2, Beiyang Chenguang Building, Shunbatiao No.1 Courtyard, Fengtai District, Beijing, China
Postal Code: 100079
Tel: 010-53879277
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ISSN 1000-0801
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