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Big Data Analytics


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  1. Content type: Research

    A comparative study of the use of bio-inspired optimization technologies including the Cuckoo Search (CS) algorithm, the Differential Evolution (DE) algorithm, and Quantum-behaved Particle Swarm Optimization (...

    Authors: Menglong He, Zhao Wang, Mark Leach, Zhenzhen Jiang and Eng Gee Lim

    Citation: Big Data Analytics 2018 3:1

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  2. Content type: Research

    Can biomarkers be used to predict the future work ability of patients admitted to hospital? To answer this question, we use a combination of biological measurements, registry data, data from questionnaires, an...

    Authors: Ove Andersen, Linda Camilla Andresen, Louise Lawson-Smith, Lea Sell and Inge Lissau

    Citation: Big Data Analytics 2017 2:11

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  3. Content type: Review

    Advertisers optimization is one of the most fundamental tasks in paid search, which is a multi-billion industry as a major part of the growing online advertising market. As paid search is a three-player game (...

    Authors: Qiufeng Wang, Kaizhu Huang, Song Li and Wei Yu

    Citation: Big Data Analytics 2017 2:8

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  4. Content type: Research

    Hot springs harbor rich bacterial diversity that could be the source of commercially important enzymes, antibiotics and many more products. Most of the hot springs present in Northeast of India are unexplored ...

    Authors: Amrita Kumari Panda, Satpal Singh Bisht, Bodh Raj Kaushal, Surajit De Mandal, Nachimuthu Senthil Kumar and Bharat C. Basistha

    Citation: Big Data Analytics 2017 2:7

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  5. Content type: Software

    In many applications where moderate to large datasets are used, plotting relationships between pairs of variables can be problematic. A large number of observations will produce a scatter-plot which is difficu...

    Authors: Sri Utami Zuliana and Aris Perperoglou

    Citation: Big Data Analytics 2017 2:6

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  6. Content type: Review

    The large amounts of data have created a need for new frameworks for processing. The MapReduce model is a framework for processing and generating large-scale datasets with parallel and distributed algorithms. ...

    Authors: Diego García-Gil, Sergio Ramírez-Gallego, Salvador García and Francisco Herrera

    Citation: Big Data Analytics 2017 2:1

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  7. Content type: Review

    Link prediction is one of the most fundamental tasks in statistical network analysis, for which latent feature models have been widely used. As large-scale networks are available in various application domains...

    Authors: Jun Zhu and Bei Chen

    Citation: Big Data Analytics 2017 2:3

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  8. Content type: Review

    Clustering is a key data mining task. This is the problem of partitioning a set of observations into clusters such that the intra-cluster observations are similar and the inter-cluster observations are dissimi...

    Authors: Mohammed Ghesmoune, Mustapha Lebbah and Hanene Azzag

    Citation: Big Data Analytics 2016 1:13

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  9. Content type: Review

    Neuromorphic Engineering has emerged as an exciting research area, primarily owing to the paradigm shift from conventional computing architectures to data-driven, cognitive computing. There is a diversity of w...

    Authors: Sumit Soman, jayadeva and Manan Suri

    Citation: Big Data Analytics 2016 1:15

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  10. Content type: Review

    The massive growth in the scale of data has been observed in recent years being a key factor of the Big Data scenario. Big Data can be defined as high volume, velocity and variety of data that require a new hi...

    Authors: Salvador García, Sergio Ramírez-Gallego, Julián Luengo, José Manuel Benítez and Francisco Herrera

    Citation: Big Data Analytics 2016 1:9

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  11. Content type: Research

    Data-based modeling is becoming practical in predicting outcomes. In the era of big data, two practically conflicting challenges are eminent: (1) the prior knowledge on the subject is largely insufficient; (2)...

    Authors: Yi Wang, Yi Li, Momiao Xiong, Yin Yao Shugart and Li Jin

    Citation: Big Data Analytics 2016 1:12

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  12. Content type: Research

    Mixed Order Hyper Networks (MOHNs) are a type of neural network in which the interactions between inputs are modelled explicitly by weights that can connect any number of neurons. Such networks have a human re...

    Authors: Kevin Swingler

    Citation: Big Data Analytics 2016 1:8

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  13. Content type: Research

    To ensure the output quality, current crowdsourcing systems highly rely on redundancy of answers provided by multiple workers with varying expertise, however massive redundancy is very expensive and time-consu...

    Authors: Man-Ching Yuen, Irwin King and Kwong-Sak Leung

    Citation: Big Data Analytics 2016 1:14

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  14. Content type: Research

    Human movement such as physical work, exercise and sport activities can be analyzed to determine kinetic (force) and kinematic (motion) characteristics. In the past, proper assessment of force variables requir...

    Authors: Andrew C. Fry, Trent J. Herda, Adam J. Sterczala, Michael A. Cooper and Matthew J. Andre

    Citation: Big Data Analytics 2016 1:11

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  15. Content type: Research

    Deep learning techniques, particularly convolutional neural networks (CNNs), are poised for widespread application in the research fields of information retrieval and natural language processing. However, ther...

    Authors: Yan Yan, Xu-Cheng Yin, Bo-Wen Zhang, Chun Yang and Hong-Wei Hao

    Citation: Big Data Analytics 2016 1:7

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  16. Content type: Editorial

    We would like to welcome you to Big Data Analytics, a pioneering multi-disciplinary open access and peer-reviewed journal, which welcomes cutting-edge articles describing biologically-inspired computational, theo...

    Authors: Amir Hussain and Asim Roy

    Citation: Big Data Analytics 2016 1:4

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2016 Journal Metrics

  • Speed
    43 days from submission to first decision
    25 days from acceptance to publication

    527.0 Usage Factor

    Social Media Impact
    101 mentions