rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Data Science and Big Data Analytics
    sub title: ACM-WIR 2018
  name:
    name part: Mishra, Durgesh Kumar.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Yang, Xin-She.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: Unal, Aynur.
    role:
      role term: editor.
    role:
      role term: edt
    role:
      role term: http://id.loc.gov/vocabulary/relators/edt
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXIV, 406 p. 152 illus., 95 illus. in color. online resource.
  abstract: This book presents conjectural advances in big data analysis, machine learning and computational intelligence, as well as their potential applications in scientific computing. It discusses major issues pertaining to big data analysis using computational intelligence techniques, and the conjectural elements are supported by simulation and modelling applications to help address real-world problems. An extensive bibliography is provided at the end of each chapter. Further, the main content is supplemented by a wealth of figures, graphs, and tables, offering a valuable guide for researchers in the field of big data analytics and computational intelligence.
  table of contents: A Study of the Correlation between Internet Addiction and Aggressive Behavior Among the Namibian University Students -- An efficient model for outlier detection in time series dataset using clustering approach -- Genetic Algorithm Approach for Optimization of Biomass Estimation at LiDAR -- E-ALIVE: An Integrated Platform Based on Machine Learning Techniques to Aware and Educate Common People with the Current Statistics of Maternal and Child Health Care -- An Effective TCP's Congestion Control Approach for Cross Layer Design in MANET -- A Study on Applying Agile Methodology to Manufacturing Industry Cloud Applications -- Baron-Cohen Model based Personality Classification using Ensemble Learning -- Analysis of Routing Protocols for Large Scale Multihop Multirate MANETs -- Review on Internet Traffic Sharing using Markov Chain Model in Computer Network -- Protein Sequence of Dengue Virus Classification and Secondary Structure Prediction using Random Forest Classifier -- Anomaly detection using Dynamic Sliding Window in Wireless Body Area Networks -- Scalable Privacy preservation in Big Data with Cloud Service Access -- Effective Healthcare Services by IoT based Model of Voluntary Doctors -- Multi Layer Architectures for SQLI Detection and Prevention in Web Application Development -- Emotional State Recognition with EEG signals using Subject Independent Approach -- Development of Early Prediction Model for Epileptic Seizures -- Research Issue in data Anonymization in Electronic Health Service: A survey -- Prediction of Cervical Cancer based on the life style, habits and diseases using Regression Analysis framework -- Novel outlier detection by integration of clustering and classification -- A Study on Benefits of Big Data for Retail Industry -- Protection of User Information by using Modified Data Copy Technique in Data Mining -- Performance Analysis of Traffic at Intersection using Direction Based Clustering in VANET -- Load Balancing using Amazon Cloud Services -- A Re…
  note: edited by Durgesh Kumar Mishra, Xin-She Yang, Aynur Unal.
  subject:
    topic: Computational intelligence
  subject:
    topic: Big data
  subject:
    topic: Data mining
  subject:
    topic: Computer security
  subject:
    topic: Computational Intelligence
  subject:
    topic: Big Data
  subject:
    topic: Data Mining and Knowledge Discovery
  subject:
    topic: Systems and Data Security
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Lecture Notes on Data Engineering and Communications Technologies, 16
  identifier: 9789811076411
  identifier: https://doi.org/10.1007/978-981-10-7641-1
  record info:
    record creation date: 180801
    record change date: 20191028232825.0
    record identifier: 978-981-10-7641-1