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2016 IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

5-7 July 2016

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Displaying Results 1 - 25 of 75
  • [Front cover]

    Publication Year: 2016, Page(s):c1 - c4
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  • [Title page]

    Publication Year: 2016, Page(s): i
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  • [Copyright notice]

    Publication Year: 2016, Page(s): ii
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  • Table of contents

    Publication Year: 2016, Page(s):iii - ix
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  • Reforming education sector through Big Data

    Publication Year: 2016, Page(s):3 - 8
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (193 KB) | HTML iconHTML

    Big data, which is maturing over time, has a high impact in analyzing scenarios and coming up with decision making strategies pertaining to any sector. Consequently the number of applications are also increasing where in the past, they were limited to the confines of company sales departments. In lieu, this paper is primarily focused on applying Data Sciences within the education sector. We will b... View full abstract»

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  • Study on the mobile cloud framework for sociology: An empirical implementation

    Publication Year: 2016, Page(s):9 - 14
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (574 KB) | HTML iconHTML

    Quantitative research has been extensively applied in sociology. The traditional way of using data statistical computing tools of R, SPSS and Stata on the stand-alone machine can't deal with the challenges of big data; furthermore, the demand of complex computing in mobile condition is increasing due to the fieldwork characteristics of sociological researchers. Considering the computing needs of s... View full abstract»

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  • Group learning analysis and individual learning diagnosis from the perspective of Big Data

    Publication Year: 2016, Page(s):15 - 21
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1249 KB) | HTML iconHTML

    This paper takes a blended course as an example in moodle platform. As a case study, multiple methods including statistical analysis, visualization and social network analysis were used to analyze the process and results of online learning. With the concept of Big Data, it analyzes 22 classes of 1088 students and teachers from a comprehensive perspective. It includes the access behavior, resource ... View full abstract»

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  • Big data analysis for Chinese women academicians management

    Publication Year: 2016, Page(s):22 - 25
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (434 KB) | HTML iconHTML

    Women are active in the field of scientific research today. A large number women scientific talents have made outstanding contributions to the progress of science and technology. Female academicians of Chinese Academy of Science (CAS) and Chinese Academy of Engineering (CAE) stand as perfect examples of high-end female scientific talents. Taking female academicians as an example, some characterist... View full abstract»

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  • Research on the big data construction of equipment support

    Publication Year: 2016, Page(s):26 - 31
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (242 KB) | HTML iconHTML

    This paper analyses the main work of equipment support from three aspects of the equipment life-cycle, support object and support work, analyses the main data and data source from the equipment life-cycle systematically, discusses the four main features of high capacity, diversification, rapidity and low density of the data in the field of equipment support, analyses the existing problems in the c... View full abstract»

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  • Semantic description and link construction of smart tourism linked data based on big data

    Publication Year: 2016, Page(s):32 - 36
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (361 KB) | HTML iconHTML

    In big data environment, the key of smart tourism information system is the method of semantic description and link construction to complete intensive, intelligent and unified management of tourism. We proposed a hierarchical semantic description framework of tourism Linked Data, which consists of 4 layers: Metadata Layer, Ontology Layer, Linked Data Layer, Data application Layer. Main roles of th... View full abstract»

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  • Big data stream computing in healthcare real-time analytics

    Publication Year: 2016, Page(s):37 - 42
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (882 KB) | HTML iconHTML

    The healthcare industry is changing at a dramatic rate. There are multiple processes going on within the health sector. These processes not only impact the care of individuals but also help medical practitioners and the delivery of care and services. The industry can take advantage of big data analytics to ensure that all the multiple processes within the industry are running smoothly. Big data an... View full abstract»

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  • Hybrid non-linear dimensionality reduction method framework based on random projections

    Publication Year: 2016, Page(s):43 - 48
    Cited by:  Papers (2)
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (822 KB) | HTML iconHTML

    Dimensionality reduction of big data is becoming more and more important in many domains, such as cloud computing, human gene distribution, image processing and smart grids, which all involve high-dimensional data analysis. While traditional linear dimensionality reduction techniques are computationally efficient and simple to implement, they fail to adequately capture the intrinsic structure of c... View full abstract»

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  • Keyword search on form result with hybrid approach

    Publication Year: 2016, Page(s):49 - 54
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1723 KB) | HTML iconHTML

    Keyword search in relational databases provides a simple and interactive query interface for retrieving data from databases. In recent year's keyword search over structured or unstructured data received significant attention. KWS performs on enterprise applications based on various forms which can take some values, these values might be express verifiable, for example user identification. A large ... View full abstract»

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  • Design and realization of learning emotion database

    Publication Year: 2016, Page(s):57 - 61
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1044 KB) | HTML iconHTML

    Expression image is depended on analyzing and studying about emotions based on expression recognition technology. However, in-depth research of emotional analysis cannot be supported because of the limited sample size, the shot scene set in constrained environment like laboratory and image with simple labeling expression information. In order to solve these issues, LDA learning emotion database is... View full abstract»

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  • Cloud storage encryption security analysis

    Publication Year: 2016, Page(s):62 - 65
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (373 KB) | HTML iconHTML

    With the increase of network bandwidth and the popularity of Internet, cloud storage has become one of the most widely used of cloud computing. Since the user may have a variety of terminal such as PC, notebook computers, tablet PCs and smart phones, and may access data in different places and on different terminal, cloud storage provides the most suitable solution to share data between these devi... View full abstract»

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  • Design and implementation of SSD aware Heterogeneous cache Algorithm: A Two-level caching algorithm for RAID storage systems

    Publication Year: 2016, Page(s):66 - 71
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (410 KB) | HTML iconHTML

    Existing conventional RAID storage systems are unable to provide expected storage performance under the explosive growth in data volumes. One of the solution is introducing SSDs (Solid State Drives), a promising storage medium which provides high performance and power efficiency, as a cache to loosen the performance bottleneck of RAID storage systems. However, using DRAM as a universe buffer area ... View full abstract»

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  • The research and implementation of metadata cache backup technology based on CEPH file system

    Publication Year: 2016, Page(s):72 - 77
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1247 KB) | HTML iconHTML

    Based on research and analysis of the Ceph file system, the log cache backup scheme is proposed. The log cache backup scheme reduces metadata access delays by caching logs and reducing the time of storing logs to server clusters. In order to prevent the loss of cached data in metadata servers, a cached data backup scheme is proposed. Compared to the metadata management subsystem of the Ceph, the l... View full abstract»

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  • Enhancing parallel k-means using map reduce for discovering knowledge from big data

    Publication Year: 2016, Page(s):81 - 87
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (831 KB) | HTML iconHTML

    Knowledge discovery from data using clustering algorithm include stages of data preprocessing, clustering the preprocessed dataset and evaluating patterns for obtaining knowledge. Along with the popularity of Hadoop, k-Means algorithm has been enhanced based on MapReduce for clustering big dataset. We enhance this existing algorithm such that it includes the capabilities for performing data prepro... View full abstract»

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  • The application of K-means clustering algorithm based on Hadoop

    Publication Year: 2016, Page(s):88 - 92
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (838 KB) | HTML iconHTML

    Spatial data is different from the general data, it not only contains some kind of property information of space feature, but also has the spatial feature of space or location. The spatial clustering analysis can be divided into two broad categories. Category from GIS theory and technology tools, according to an object of spatial geographical coordinates, cluster as an object of the spatial proxim... View full abstract»

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  • The improvement and application of a K-means clustering algorithm

    Publication Year: 2016, Page(s):93 - 96
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (807 KB) | HTML iconHTML

    This paper proposes a K-means algorithm with the dynamic adjustable number of clusters. The algorithm uses the improved Euclidean distance formula to calculate the distance between the cluster center and data, by judging whether the distance is greater than the threshold to automatically adjust the number of clusters. Finally, the improved algorithm is applied to intrusion detection system to dete... View full abstract»

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  • The functional structure evolution of Shandong Peninsula Urban Agglomeration

    Publication Year: 2016, Page(s):97 - 101
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (806 KB) | HTML iconHTML

    By using the data of city function of Shandong Peninsula Urban Agglomeration (SDPUA) in 2004, 2009 and 2014, Location quotient, K-means clustering algorithm and ARCGIS10.0 were applied to analyze the functional structure evolution of SDPUA. The results show that the cities functions and their evolution exist obvious regional differences. for example the dominant and strong functions of Jinan are c... View full abstract»

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  • Demographic transformation and clustering of transactional data for sales prediction of convenience stores

    Publication Year: 2016, Page(s):102 - 108
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1646 KB) | HTML iconHTML

    Reliable retail sales prediction of convenience stores (CVSs) can not only help in making correct purchase decision but also in determining which new products to be launched. Therefore, the main aim of this paper is to propose an enhanced method based on clustering and different abstraction forms of data to forecast the retail sales of CVSs. We use customer type proportion to calculate the similar... View full abstract»

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  • Multi-view clustering via graph regularized symmetric nonnegative matrix factorization

    Publication Year: 2016, Page(s):109 - 114
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1473 KB) | HTML iconHTML

    Multi-view clustering has become a hot topic since the past decade and nonnegative matrix factorization (NMF) based multi-view clustering algorithms have shown their superiorities. Nevertheless, two drawbacks prevent NMF based multi-view algorithms from being a better algorithm: (1) The solution of NMF based multi-view algorithms is not unique. (2) Standard orthogonal basis matrix is not obtained ... View full abstract»

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  • A multilevel K-Means algorithm for the clustering problem

    Publication Year: 2016, Page(s):115 - 121
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (722 KB) | HTML iconHTML

    Data Mining is concerned with the discovery of interesting patterns and knowledge in data repositories. Cluster Analysis which belongs to the core methods of data mining is the process of discovering homogeneous groups called clusters. Given a data-set and some measure of similarity between data objects, the goal in most clustering algorithms is maximizing both the homogeneity within each cluster ... View full abstract»

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  • A new evidence accumulation method with hierarchical clustering

    Publication Year: 2016, Page(s):122 - 126
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (615 KB) | HTML iconHTML

    Evidence accumulation clustering is widely used with the developing of data mining. With the coming of the era of big data, it is inevitable that the clustering will be used in big data. This paper proposed a new evidence accumulation clustering with hierarchical clustering method. It clusters a feature one by one rather than clustering all features at the same time. The algorithm uses voting mech... View full abstract»

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