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  • Open Access

    ARTICLE

    Security and Privacy Frameworks for Access Control Big Data Systems

    Paolina Centonze1,*

    CMC-Computers, Materials & Continua, Vol.59, No.2, pp. 361-374, 2019, DOI:10.32604/cmc.2019.06223

    Abstract In the security and privacy fields, Access Control (AC) systems are viewed as the fundamental aspects of networking security mechanisms. Enforcing AC becomes even more challenging when researchers and data analysts have to analyze complex and distributed Big Data (BD) processing cluster frameworks, which are adopted to manage yottabyte of unstructured sensitive data. For instance, Big Data systems’ privacy and security restrictions are most likely to failure due to the malformed AC policy configurations. Furthermore, BD systems were initially developed toped to take care of some of the DB issues to address BD challenges and… More >

  • Open Access

    ARTICLE

    Semantics Analytics of Origin-Destination Flows from Crowd Sensed Big Data

    Ning Cao1,2, Shengfang Li1, Keyong Shen1, Sheng Bin3, Gengxin Sun3,*, Dongjie Zhu4, Xiuli Han5, Guangsheng Cao5, Abraham Campbell6

    CMC-Computers, Materials & Continua, Vol.61, No.1, pp. 227-241, 2019, DOI:10.32604/cmc.2019.06125

    Abstract Monitoring, understanding and predicting Origin-destination (OD) flows in a city is an important problem for city planning and human activity. Taxi-GPS traces, acted as one kind of typical crowd sensed data, it can be used to mine the semantics of OD flows. In this paper, we firstly construct and analyze a complex network of OD flows based on large-scale GPS taxi traces of a city in China. The spatiotemporal analysis for the OD flows complex network showed that there were distinctive patterns in OD flows. Then based on a novel complex network model, a semantics More >

  • Open Access

    ARTICLE

    Collaborative Filtering Recommendation Algorithm Based on Multi-Relationship Social Network

    Sheng Bin1,*, Gengxin Sun1, Ning Cao2, Jinming Qiu2, Zhiyong Zheng3, Guohua Yang4, Hongyan Zhao5, Meng Jiang6, Lina Xu7

    CMC-Computers, Materials & Continua, Vol.60, No.2, pp. 659-674, 2019, DOI:10.32604/cmc.2019.05858

    Abstract Recommendation system is one of the most common applications in the field of big data. The traditional collaborative filtering recommendation algorithm is directly based on user-item rating matrix. However, when there are huge amounts of user and commodities data, the efficiency of the algorithm will be significantly reduced. Aiming at the problem, a collaborative filtering recommendation algorithm based on multi-relational social networks is proposed. The algorithm divides the multi-relational social networks based on the multi-subnet complex network model into communities by using information dissemination method, which divides the users with similar degree into a community. More >

  • Open Access

    ARTICLE

    Research on the Law of Garlic Price Based on Big Data

    Feng Guo1, Pingzeng Liu1,*, Chao Zhang1, Weijie Chen1, Wei Han2, Wanming Ren4, Yong Zheng4, Jianrui Ding3

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 795-808, 2019, DOI:10.32604/cmc.2019.03795

    Abstract In view of the frequent fluctuation of garlic price under the market economy and the current situation of garlic price, the fluctuation of garlic price in the circulation link of garlic industry chain is analyzed, and the application mode of multidisciplinary in the agricultural industry is discussed. On the basis of the big data platform of garlic industry chain, this paper constructs a Garch model to analyze the fluctuation law of garlic price in the circulation link and provides the garlic industry service from the angle of price fluctuation combined with the economic analysis. The More >

  • Open Access

    ARTICLE

    Dynamic Trust Model Based on Service Recommendation in Big Data

    Gang Wang1,*, Mengjuan Liu2

    CMC-Computers, Materials & Continua, Vol.58, No.3, pp. 845-857, 2019, DOI:10.32604/cmc.2019.03678

    Abstract In big data of business service or transaction, it is impossible to provide entire information to both of services from cyber system, so some service providers made use of maliciously services to get more interests. Trust management is an effective solution to deal with these malicious actions. This paper gave a trust computing model based on service-recommendation in big data. This model takes into account difference of recommendation trust between familiar node and stranger node. Thus, to ensure accuracy of recommending trust computing, paper proposed a fine-granularity similarity computing method based on the similarity of More >

  • Open Access

    ARTICLE

    Research on the Relationship Between Garlic and Young Garlic Shoot Based on Big Data

    Feng Guo1, Pingzeng Liu1,*, Wanming Ren2, Ning Cao3, Chao Zhang1, Fujiang Wen1, Helen Min Zhou4

    CMC-Computers, Materials & Continua, Vol.58, No.2, pp. 363-378, 2019, DOI:10.32604/cmc.2019.03794

    Abstract In view of the problems such as frequent fluctuation of garlic price, lack of efficient forecasting means and difficulty in realizing the steady development of garlic industry, combined with the current situation of garlic industry and the collected data information. Taking Big Data platform of garlic industry chain as the core, using the methods of correlation analysis, smoothness test, co-integration test, and Granger causality test, this paper analyzes the correlation, dynamic, and causality between garlic price and young garlic shoot price. According to the current situation of garlic industry, the garlic industry service based on More >

  • Open Access

    ARTICLE

    Development and Application of Big Data Platform for Garlic Industry Chain

    Weijie Chen1, Guo Feng1, Chao Zhang1, Pingzeng Liu1,*, Wanming Ren2, Ning Cao3, Jianrui Ding4

    CMC-Computers, Materials & Continua, Vol.58, No.1, pp. 229-248, 2019, DOI:10.32604/cmc.2019.03743

    Abstract In order to effectively solve the problems which affect the stable and healthy development of garlic industry, such as the uncertainty of the planting scale and production data, the influence factors of price fluctuation is difficult to be accurately analyzed, the difficult to predict the trend of price change, the uncertainty of the market concentration, and the difficulty of the short-term price prediction etc. the big data platform of the garlic industry chain has been developed. Combined with a variety of data acquisition technology, the information collection of influencing factors for garlic industry chain is More >

  • Open Access

    ARTICLE

    Forensic Investigation Through Data Remnants on Hadoop Big Data Storage System

    Myat Nandar Oo1, Sazia Parvin2, Thandar Thein3

    Computer Systems Science and Engineering, Vol.33, No.3, pp. 203-217, 2018, DOI:10.32604/csse.2018.33.203

    Abstract Forensic examiners are in an uninterrupted battle with criminals in the use of Big Data technology. The underlying storage system is the main scene to trace the criminal activities. Big Data Storage System is identified as an emerging challenge to digital forensics. Thus, it requires the development of a sound methodology to investigate Big Data Storage System. Since the use of Hadoop as Big Data Storage System continues to grow rapidly, investigation process model for forensic analysis on Hadoop Storage and attached client devices is compulsory. Moreover, forensic analysis on Hadoop Big Data Storage System More >

  • Open Access

    ARTICLE

    Sentiment Analysis System in Big Data Environment

    Wint Nyein Chan1, Thandar Thein2

    Computer Systems Science and Engineering, Vol.33, No.3, pp. 187-202, 2018, DOI:10.32604/csse.2018.33.187

    Abstract Nowadays, Big Data, a large volume of both structured and unstructured data, is generated from Social Media. Social Media are powerful marketing tools and social big data can offer the business insights. The major challenge facing social big data is attaining efficient techniques to collect a large volume of social data and extract insights from the huge amount of collected data. Sentiment Analysis of social big data can provide business insights by extracting the public opinions. The traditional analytic platforms need to be scaled up for analyzing a large volume of social big data. Social… More >

  • Open Access

    ARTICLE

    Automated and Precise Event Detection Method for Big Data in Biomedical Imaging with Support Vector Machine

    Lufeng Yuan, Erlin Yao, Guangming Tan

    Computer Systems Science and Engineering, Vol.33, No.2, pp. 105-113, 2018, DOI:10.32604/csse.2018.33.105

    Abstract This paper proposes a machine learning based method which can detect certain events automatically and precisely in biomedical imaging. We detect one important and not well-defined event, which is called flash, in fluorescence images of Escherichia coli. Given a time series of images, first we propose a scheme to transform the event detection on region of interest (ROI) in images to a classification problem. Then with supervised human labeling data, we develop a feature selection technique to utilize support vector machine (SVM) to solve this classification problem. To reduce the time in training SVM model,… More >

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