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  1. Review

    Adaptive modeling for large-scale advertisers optimization

    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 (...

    Qiufeng Wang, Kaizhu Huang, Song Li and Wei Yu

    Big Data Analytics 2017 2:8

    Published on: 31 August 2017

  2. Research

    Bacterial diversity analysis of Yumthang hot spring, North Sikkim, India by Illumina sequencing

    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 ...

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

    Big Data Analytics 2017 2:7

    Published on: 20 August 2017

  3. Software

    Two dimensional smoothing via an optimised Whittaker smoother

    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...

    Sri Utami Zuliana and Aris Perperoglou

    Big Data Analytics 2017 2:6

    Published on: 13 March 2017

  4. Review

    Latent feature models for large-scale link prediction

    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...

    Jun Zhu and Bei Chen

    Big Data Analytics 2017 2:3

    Published on: 1 February 2017

  5. Review

    State-of-the-art on clustering data streams

    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...

    Mohammed Ghesmoune, Mustapha Lebbah and Hanene Azzag

    Big Data Analytics 2016 1:13

    Published on: 1 December 2016

  6. Review

    Recent trends in neuromorphic engineering

    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...

    Sumit Soman, jayadeva and Manan Suri

    Big Data Analytics 2016 1:15

    Published on: 1 December 2016

  7. Review

    Big data preprocessing: methods and prospects

    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...

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

    Big Data Analytics 2016 1:9

    Published on: 1 November 2016

  8. Research

    Random bits regression: a strong general predictor for big data

    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)...

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

    Big Data Analytics 2016 1:12

    Published on: 1 November 2016

  9. Research

    Structure discovery in mixed order hyper networks

    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...

    Kevin Swingler

    Big Data Analytics 2016 1:8

    Published on: 1 October 2016

  10. Research

    Semantic indexing with deep learning: a case study

    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...

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

    Big Data Analytics 2016 1:7

    Published on: 30 August 2016

  11. Review

    Big data for development: applications and techniques

    With the explosion of social media sites and proliferation of digital computing devices and Internet access, massive amounts of public data is being generated on a daily basis. Efficient techniques/algorithms ...

    Anwaar Ali, Junaid Qadir, Raihan ur Rasool, Arjuna Sathiaseelan, Andrej Zwitter and Jon Crowcroft

    Big Data Analytics 2016 1:2

    Published on: 1 July 2016

  12. Research

    Leveraging big data in population health management

    Population health management takes into account many determinants of health, including medical care, social and physical environments and related services, genetics, and individual behavior. Many different typ...

    Timothy S. Wells, Ronald J. Ozminkowski, Kevin Hawkins, Gandhi R. Bhattarai and Douglas G. Armstrong

    Big Data Analytics 2016 1:1

    Published on: 1 July 2016

  13. Review

    Survey on data science with population-based algorithms

    This paper discusses the relationship between data science and population-based algorithms, which include swarm intelligence and evolutionary algorithms. We reviewed two categories of literature, which include...

    Shi Cheng, Bin Liu, T. O. Ting, Quande Qin, Yuhui Shi and Kaizhu Huang

    Big Data Analytics 2016 1:3

    Published on: 1 July 2016

  14. Editorial

    The emerging era of Big Data Analytics

    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...

    Amir Hussain and Asim Roy

    Big Data Analytics 2016 1:4

    Published on: 1 July 2016

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