By Topic

2017 IEEE 2nd International Conference on Cloud Computing and Big Data Analysis (ICCCBDA)

28-30 April 2017

Filter Results

Displaying Results 1 - 25 of 105
  • [Front cover]

    Publication Year: 2017, Page(s):c1 - c4
    Request permission for commercial reuse | PDF file iconPDF (3316 KB)
    Freely Available from IEEE
  • [Copyright notice]

    Publication Year: 2017, Page(s):1 - 2
    Request permission for commercial reuse | PDF file iconPDF (56 KB)
    Freely Available from IEEE
  • Preface

    Publication Year: 2017, Page(s): xi
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (22 KB)

    2017 the 2nd IEEE International Conference on Cloud Computing and Big Data Analysis (ICCCBDA 2017) is a comprehensive conference which focuses on cloud computing and big data analysis. The main goal of the conference is to address and deliberate on the latest technical status and recent trends in the research and applications of cloud computing and big data analysis. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Conference committees

    Publication Year: 2017, Page(s):xii - xiii
    Request permission for commercial reuse | PDF file iconPDF (35 KB)
    Freely Available from IEEE
  • Table of contents

    Publication Year: 2017, Page(s):iii - x
    Request permission for commercial reuse | PDF file iconPDF (122 KB)
    Freely Available from IEEE
  • Author index

    Publication Year: 2017, Page(s):542 - 545
    Request permission for commercial reuse | PDF file iconPDF (35 KB)
    Freely Available from IEEE
  • Measurement for social network data currency and trustworthiness

    Publication Year: 2017, Page(s):1 - 5
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (366 KB) | HTML iconHTML

    Along with the explosive growth of the information in Social Network Service, the research of the quality of data has become a new hot point in related research field. High quality social data can more effectively support data mining, knowledge discovery, and can provide reliable and efficient data for users. Based on the measure problems of data quality, this paper discussed the measurement of tw... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Improving availability and confidentiality of shared data under the multi-cloud environment

    Publication Year: 2017, Page(s):6 - 10
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (680 KB) | HTML iconHTML

    Current providers of the cloud storage service often ensure the data confidentiality by encrypting the file content and guarantee the data integrity by verifying the hash value of the file. However, when the cloud storage service fails, the availability of the user data cannot be guaranteed and nor can the cloud sharing function of the user data be supported. In addition, users have to give the pr... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • SNSQ ontology: A domain ontology for SNSs data quality

    Publication Year: 2017, Page(s):11 - 18
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1842 KB) | HTML iconHTML

    the advent of online social networks has been one of the most exciting events in this decade. Many popular online social networks such as Twitter, Wechat, Weibo, LinkedIn, and Facebook have become increasingly popular. The consequences of the poor quality of data in a social network are often experienced in everyday life. This paper gives a domain ontology model, SNSQ Ontology, for data quality in... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A conflict conciliation strategy in data integration

    Publication Year: 2017, Page(s):19 - 23
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (838 KB) | HTML iconHTML

    The advancements of Internet accelerate the intelligent process of data integration in recent years. When fusing a volume of records about the same real-world entity into a single, consistent and clean representation, appropriate conflicts conciliation becomes essential for participants. This paper advocates a strategic framework for perceiving and resolving data inconsistencies via employing trut... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Feature extraction and evaluation of electricity load data with high precision

    Publication Year: 2017, Page(s):24 - 28
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (905 KB) | HTML iconHTML

    This paper summarizes the characteristics of the electricity load data collected every 15 minutes of power users. The single-day load data of single power user is taken as a 96-length vector, and the single-day data of n users is taken as a 96-column set. Single-user monthly data and annual data are described as a 30 (31) × 96 matrix and a 365 (366) × 96 matrix respectively. By compa... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Research on cloud computing for disaster monitoring using massive remote sensing data

    Publication Year: 2017, Page(s):29 - 33
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (494 KB) | HTML iconHTML

    Satellite remote sensing technology can extract disaster information rapidly and accurately for disaster monitoring on a regional or national basis. However, various sensors are generating huge volumes of remote sensing data for disaster management. It is urgent to handle such massive remote sensing images. In this paper, it provides the solutions for massive remote sensing data analysis and rapid... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Study of power grid development diagnosis system based on multi-source data analysis

    Publication Year: 2017, Page(s):34 - 38
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1124 KB) | HTML iconHTML

    In view of the current problems of miscellaneous data channel, huge-scale information and rough evaluation method in power grid development diagnosis analysis, a study of power grid development diagnosis system is conducted based on multi-source data analysis. With the interface to product management system (PMS), energy management system (EMS), distribution automation system (DAS), electric infor... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A modified evidence theory model for data fusion

    Publication Year: 2017, Page(s):39 - 43
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (705 KB) | HTML iconHTML

    To overcome the drawbacks of traditional convex evidence, in this paper we proposed a modified convex evidence theory model, we presented the modified combination function and use it to combine mass function of ordered propositions, we present the calculation of the parameters of the proposed combination function, and proposed a more accurate method to find the proposition which is most likely tru... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimizing small file storage process of the HDFS which based on the indexing mechanism

    Publication Year: 2017, Page(s):44 - 48
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (533 KB)

    As an open source implementation of GFS, Hadoop Distributed File System (HDFS) has high efficiency on handling the large files. However, due to its own master-slave structure and the storage of metadata, the efficiency is low when dealing with massive small files. It occupies large amount of NameNode memory, reduces access efficiency, and delays concurrent user access. In order to improve this per... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Medical data classification scheme based on hybridized SMOTE technique (HST) and Rough Set technique (RST)

    Publication Year: 2017, Page(s):49 - 55
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1594 KB) | HTML iconHTML

    Medical data are extensively used in the diagnosis of human health. So it has played a vital role for physicians as well as in medical engineering. Accordingly, many types of research are going on related to this to have a better prediction of the diseases or to improve the diagnosis quality. However, most of the researchers work on either dimensionality space or imbalanced data. Due to this, some... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Privacy preserving and performance analysis on not only SQL database aggregation in bigdata era

    Publication Year: 2017, Page(s):56 - 60
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (691 KB) | HTML iconHTML

    Database management systems have been indispensable to enterprises for decades. As the amount of data dramatically increased, database aggregation has encountered a dilemma between privacy and performance. In traditional database aggregation, all attributes have been encrypted to protect the privacy of data. However, in big data, this privacy measure is no longer feasible because cryptography will... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A distinctive transformation approach of NoSQL's SQL conditions based on Espresso

    Publication Year: 2017, Page(s):61 - 69
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (310 KB) | HTML iconHTML

    Recently, numerous NoSQL (Not Only SQL) data-store systems have been developed, which often involve Big Data processing. Importantly, there are no common standard APIs for accessing the different NoSQL systems. In order to solve the problem, many scholars have used different techniques to build SQL access layer for different NoSQL databases. Meanwhile another problem related to this topic needs to... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Application of anomaly detection for detecting anomalous records of terroris attacks

    Publication Year: 2017, Page(s):70 - 75
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (404 KB) | HTML iconHTML

    Nowadays, terrorism has evolved into such a destructive threat to the whole world that it is calling for an increasing devotion of professional researches and explorations. Machine learning, as a powerful weapon to unveil the hidden knowledge, has been successfully applied into the anti-terrorism field. The aim of this paper is as follows: by implementing anomaly detection algorithm into a famous ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Optimization of cache-based semi-stream joins

    Publication Year: 2017, Page(s):76 - 81
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1153 KB) | HTML iconHTML

    Near-real-time data warehousing is an emerging area of research in order to meet the high and up-to-date demands of business organizations. This means customers transactions executed at data source level need to reflect into the data warehouse immediately that requires semi-stream join between a stream of customer transactions and disk-based master data. For this purpose a well-known algorithm cal... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Application of kNN improved algorithm in automatic classification of network public proposal cases

    Publication Year: 2017, Page(s):82 - 86
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (1199 KB) | HTML iconHTML

    With the rapid development of information technology, the concept of big data is used in information collection on different things, especially for the text classification. This paper propose an improved KNN algorithm based on clustering for the automatic classification of Web text. In addition, we find a new method to find out which text in the same category belongs to the same cluster. Finally, ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Multi-granularity grey incidence measurement method to data distribution sequence

    Publication Year: 2017, Page(s):87 - 92
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (675 KB) | HTML iconHTML

    The data distribution sequence is an important tool in data compression and data storage area. The traditional grey incidence measurement method is mainly focus on the accurate numerical sequences, and lacks of the effective analysis and data mining tools to the mixed type sequence (such as sequence contains grey numbers, fuzzy numbers, random numbers, etc.) Based on the specified partition in seq... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Research on optimized R-Tree high-dimensional indexing method based on video features

    Publication Year: 2017, Page(s):93 - 97
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (409 KB) | HTML iconHTML

    In order to solve the dimension disaster problem of Video high dimensional feature, a new indexing method is proposed: PKSR-Tree index. PKSR-Tree index first uses the principal component analysis to reduce the dimensionality of the high-dimensional feature data, reducing the dimension of the disaster impact and making the distribution of data homogeneous. The feature data after dimensionality redu... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • S-FPG: A parallel version of FP-Growth algorithm under Apache Spark™

    Publication Year: 2017, Page(s):98 - 101
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (710 KB) | HTML iconHTML

    Frequent Itemsets Mining (FIM) is an essential data mining task, with many real world applications such as market basket analysis, outlier detection, and so one. Many efficient single-node FIM algorithms such as the well-known FP-Growth algorithm have been proposed in the last two decades. However, as large-scale datasets are usually adopted nowadays, these algorithms become inefficient to mine fr... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Mining potential proteins as drug targets using ensemble models

    Publication Year: 2017, Page(s):102 - 107
    Request permission for commercial reuse | Click to expandAbstract | PDF file iconPDF (588 KB) | HTML iconHTML

    Mining drug targets from database is a problem of challenge but significance, which has received much attention from academia and industry. As a main source of drug targets, proteins have abundant sequence properties analyzed by the modern measuring techniques and those properties provide a new perspective for detecting the potential proteins as drug targets. In our research, two typical ensemble ... View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.