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  2. Data visuals (scientific images) display and express various amounts and types of information, and, as the saying goes,“an image is worth 1,000 words.” Based on a review of two studies, a new estimation of how...

    Authors: Mohamed Elgendi, Newton Howard, Amir Hussain, Carlo Menon and Rabab Ward

    Citation: Big Data Analytics 2020 5:4

    Content type: Commentary

    Published on:

  5. As the scope of scientific questions increase and datasets grow larger, the visualization of relevant information correspondingly becomes more difficult and complex. Sharing visualizations amongst collaborator...

    Authors: Jordan K. Matelsky, Joseph Downs, Hannah P. Cowley, Brock Wester and William Gray-Roncal

    Citation: Big Data Analytics 2020 5:1

    Content type: Software

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  7. Data preprocessing techniques are devoted to correcting or alleviating errors in data. Discretization and feature selection are two of the most extended data preprocessing techniques. Although we can find many...

    Authors: Alejandro Alcalde-Barros, Diego García-Gil, Salvador García and Francisco Herrera

    Citation: Big Data Analytics 2019 4:4

    Content type: Software

    Published on:

  9. Associative Classification, a combination of two important and different fields (classification and association rule mining), aims at building accurate and interpretable classifiers by means of association rul...

    Authors: Francisco Padillo, José María Luna and Sebastián Ventura

    Citation: Big Data Analytics 2019 4:2

    Content type: Research

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  10. Emerging pattern mining is a data mining task that extracts rules describing discriminative relationships amongst variables. These rules should be understandable for the experts. Comprehensibility of a rule is...

    Authors: Ángel Miguel García-Vico, Pedro González, Cristóbal José Carmona and María José del Jesus

    Citation: Big Data Analytics 2019 4:1

    Content type: Research

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  11. In matrix completion fields, the traditional convex regularization may fall short of delivering reliable low-rank estimators with good prediction performance. Previous works use the alternation least squares a...

    Authors: Xiao-Bo Jin, Guo-Sen Xie, Qiu-Feng Wang, Guoqiang Zhong and Guang-Gang Geng

    Citation: Big Data Analytics 2018 3:11

    Content type: Research

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  12. The emerging of depth-camera technology is paving the way for variety of new applications and it is believed that plane detection is one of them. In fact, planes are common in man-made living structures, thus ...

    Authors: Zhi Jin, Tammam Tillo, Wenbin Zou, Xia Li and Eng Gee Lim

    Citation: Big Data Analytics 2018 3:10

    Content type: Research

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  13. Organization of companies and their HR departments are becoming hugely affected by recent advancements in computational power and Artificial Intelligence, with this trend likely to dramatically rise in the nex...

    Authors: Julio Amador Diaz Lopez, Miguel Molina-Solana and Mark T. Kennedy

    Citation: Big Data Analytics 2018 3:9

    Content type: Review

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  16. Genome Wide Analytics Studies with regard to structural variations is a key component in phenome association. Here we analyze a family trio of father, mother and children for scientific discovery purpose.

    Authors: Abhishek Narain Singh

    Citation: Big Data Analytics 2018 3:6

    Content type: Research

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  17. Unsupervised machine-learned analysis of cluster structures, applied using the emergent self-organizing feature maps (ESOM) combined with the unified distance matrix (U-matrix) has been shown to provide an unb...

    Authors: Jörn Lötsch, Florian Lerch, Ruth Djaldetti, Irmgard Tegder and Alfred Ultsch

    Citation: Big Data Analytics 2018 3:5

    Content type: Software

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  18. One of the key technologies for future large-scale location-aware services covering a complex of multi-story buildings is a scalable indoor localization technique. In this paper, we report the current status of o...

    Authors: Kyeong Soo Kim, Sanghyuk Lee and Kaizhu Huang

    Citation: Big Data Analytics 2018 3:4

    Content type: Research

    Published on:

  19. Distance metric plays an important role in machine learning which is crucial to the performance of a range of algorithms. Metric learning, which refers to learning a proper distance metric for a particular tas...

    Authors: Peipei Yang, Kaizhu Huang and Amir Hussain

    Citation: Big Data Analytics 2018 3:3

    Content type: Review

    Published on:

  21. 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

    Content type: Research

    Published on:

  22. 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

    Content type: Research

    Published on:

  25. 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

    Content type: Review

    Published on:

  26. 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

    Content type: Research

    Published on:

  27. 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

    Content type: Software

    Published on:

  28. 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

    Content type: Review

    Published on:

  30. 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

    Content type: Review

    Published on:

  33. 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

    Content type: Review

    Published on:

  34. 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

    Content type: Review

    Published on:

  35. 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

    Content type: Research

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  36. 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

    Content type: Review

    Published on:

  37. 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

    Content type: Research

    Published on:

  38. 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

    Content type: Research

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  39. 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

    Content type: Research

    Published on:

  41. 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

    Content type: Research

    Published on:

  44. 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

    Content type: Editorial

    Published on:

  45. 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...

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

    Citation: Big Data Analytics 2016 1:3

    Content type: Review

    Published on:

  46. 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 ...

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

    Citation: Big Data Analytics 2016 1:2

    Content type: Review

    Published on:

  47. 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...

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

    Citation: Big Data Analytics 2016 1:1

    Content type: Research

    Published on:

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