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  1. Content type: Research

    The DBSCAN algorithm is a prevalent method of density-based clustering algorithms, the most important feature of which is the ability to detect arbitrary shapes and varied clusters and noise data. Nevertheless...

    Authors: Safanaz Heidari, Mahmood Alborzi, Reza Radfar, Mohammad Ali Afsharkazemi and Ali Rajabzadeh Ghatari

    Citation: Journal of Big Data 2019 6:77

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  2. Content type: Correction

    The authors note a correction to the article [1]. Table 5 of the original article is incomplete. Few percentage values are missing. This article presents the corrected version of Table 5.

    Authors: Imane El Alaoui, Youssef Gahi, Rochdi Messoussi, Youness Chaabi, Alexis Todoskoff and Abdessamad Kobi

    Citation: Journal of Big Data 2019 6:76

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    The original article was published in Journal of Big Data 2018 5:12

  3. Content type: Research

    Data scientists spend considerable amounts of time preparing data for analysis. Data preparation is labour intensive because the data scientist typically takes fine grained control over each aspect of each ste...

    Authors: Nikolaos Konstantinou, Edward Abel, Luigi Bellomarini, Alex Bogatu, Cristina Civili, Endri Irfanie, Martin Koehler, Lacramioara Mazilu, Emanuel Sallinger, Alvaro A. A. Fernandes, Georg Gottlob, John A. Keane and Norman W. Paton

    Citation: Journal of Big Data 2019 6:74

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  4. Content type: Methodology

    This study addresses the problem of traffic flow estimation based on the data from a video surveillance camera. Target problem here is formulated as counting and classifying vehicles by their driving direction...

    Authors: Aleksandr Fedorov, Kseniia Nikolskaia, Sergey Ivanov, Vladimir Shepelev and Alexey Minbaleev

    Citation: Journal of Big Data 2019 6:73

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  5. Content type: Research

    In this paper, we describe the design of a machine learning-based classifier, tailored to predict whether a water meter will fail or need a replacement. Our initial attempt to train a recurrent deep neural net...

    Authors: Marco Roccetti, Giovanni Delnevo, Luca Casini and Giuseppe Cappiello

    Citation: Journal of Big Data 2019 6:70

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  6. Content type: Research

    High class imbalance between majority and minority classes in datasets can skew the performance of Machine Learning algorithms and bias predictions in favor of the majority (negative) class. This bias, for cases ...

    Authors: Tawfiq Hasanin, Taghi M. Khoshgoftaar, Joffrey L. Leevy and Naeem Seliya

    Citation: Journal of Big Data 2019 6:69

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  7. Content type: Methodology

    In this paper, we comprehensively explain how we built a novel implementation of the Random Forest algorithm on the High Performance Computing Cluster (HPCC) Systems Platform from LexisNexis. The algorithm was...

    Authors: Victor M. Herrera, Taghi M. Khoshgoftaar, Flavio Villanustre and Borko Furht

    Citation: Journal of Big Data 2019 6:68

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  8. Content type: Case study

    Life in the city generates data on human behavior in many different ways. Measuring human behavior in terms of criminal offenses plays a critical role on identifying the most common crime type in each urban ar...

    Authors: C. A. Piña-García and Leticia Ramírez-Ramírez

    Citation: Journal of Big Data 2019 6:65

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  9. Content type: Research

    Access to affordable healthcare is a nationwide concern that impacts a large majority of the United States population. Medicare is a Federal Government healthcare program that provides affordable health insura...

    Authors: Justin M. Johnson and Taghi M. Khoshgoftaar

    Citation: Journal of Big Data 2019 6:63

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  10. Content type: Research

    The human brain is a complex system of neural tissue that varies significantly between individuals. Although the technology that delineates these neural pathways does not currently exist, medical imaging modal...

    Authors: Andrea Hart, Brianna Smith, Sean Smith, Elijah Sales, Jacqueline Hernandez-Camargo, Yarlin Mayor Garcia, Felix Zhan, Lori Griswold, Brian Dunkelberger, Michael R. Schwob, Sharang Chaudhry, Justin Zhan, Laxmi Gewali and Paul Oh

    Citation: Journal of Big Data 2019 6:61

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  11. Content type: Survey paper

    Deep convolutional neural networks have performed remarkably well on many Computer Vision tasks. However, these networks are heavily reliant on big data to avoid overfitting. Overfitting refers to the phenomen...

    Authors: Connor Shorten and Taghi M. Khoshgoftaar

    Citation: Journal of Big Data 2019 6:60

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  12. Content type: Research

    Due to the increasing popularity of recent advanced features and context-awareness in smart mobile phones, the contextual data relevant to users’ diverse activities with their phones are recorded through the d...

    Authors: Iqbal H. Sarker, A. S. M. Kayes and Paul Watters

    Citation: Journal of Big Data 2019 6:57

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  13. Content type: Survey paper

    ‘Big data’ is massive amounts of information that can work wonders. It has become a topic of special interest for the past two decades because of a great potential that is hidden in it. Various public and priv...

    Authors: Sabyasachi Dash, Sushil Kumar Shakyawar, Mohit Sharma and Sandeep Kaushik

    Citation: Journal of Big Data 2019 6:54

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  14. Content type: Research

    This paper presents our research on the development of navigation systems of autonomous drone for delivering items that uses a GNSS (Global Navigation Satellite System) and a compass as the main tools in drone...

    Authors: Aurello Patrik, Gaudi Utama, Alexander Agung Santoso Gunawan, Andry Chowanda, Jarot S. Suroso, Rizatus Shofiyanti and Widodo Budiharto

    Citation: Journal of Big Data 2019 6:53

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  15. Content type: Research

    Adversarial attacks represent a serious evolving threat to the operation of deep neural networks. Recently, adversarial algorithms were developed to facilitate hallucination of deep neural networks for ordinar...

    Authors: Alaa E. Abdel-Hakim

    Citation: Journal of Big Data 2019 6:51

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  16. Content type: Survey paper

    Recently, big data streams have become ubiquitous due to the fact that a number of applications generate a huge amount of data at a great velocity. This made it difficult for existing data mining tools, techno...

    Authors: Taiwo Kolajo, Olawande Daramola and Ayodele Adebiyi

    Citation: Journal of Big Data 2019 6:47

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  17. Content type: Research

    Data scientists need scalable methods to explore and clean big data before applying advanced data analysis and mining algorithms. In this paper, we propose the RSP-Explore method to enable data scientists to i...

    Authors: Salman Salloum, Joshua Zhexue Huang and Yulin He

    Citation: Journal of Big Data 2019 6:45

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  18. Content type: Methodology

    Data validation is about verifying the correctness of data. When organisations update and refine their data transformations to meet evolving requirements, it is imperative to ensure that the new version of a w...

    Authors: Raya Rizk, Steve McKeever, Johan Petrini and Erik Zeitler

    Citation: Journal of Big Data 2019 6:41

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  19. Content type: Methodology

    Big data architectures have been gaining momentum in recent years. For instance, Twitter uses stream processing frameworks like Apache Storm to analyse billions of tweets per minute and learn the trending topi...

    Authors: Marcello M. Bersani, Francesco Marconi, Damian A. Tamburri, Andrea Nodari and Pooyan Jamshidi

    Citation: Journal of Big Data 2019 6:40

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  20. Content type: Methodology

    Pattern mining is a powerful tool for analysing big datasets. Temporal datasets include time as an additional parameter. This leads to complexity in algorithmic formulation, and it can be challenging to proces...

    Authors: Sofya S. Titarenko, Valeriy N. Titarenko, Georgios Aivaliotis and Jan Palczewski

    Citation: Journal of Big Data 2019 6:37

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  21. Content type: Research

    We study the the spread and adoption of libraries within Python projects hosted in public software repositories on GitHub. By modelling the use of Git pull, merge, commit, and other actions as deliberate cogni...

    Authors: Rachel Krohn and Tim Weninger

    Citation: Journal of Big Data 2019 6:36

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  22. Content type: Research

    The global popularity of social media platforms has given rise to unprecedented amounts of data, much of which reflects the thoughts, opinions and affective states of individual users. Systematic explorations ...

    Authors: Aamna Al Shehhi, Justin Thomas, Roy Welsch, Ian Grey and Zeyar Aung

    Citation: Journal of Big Data 2019 6:33

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  23. Content type: Methodology

    We address the problem of detecting highly raised crowd density in situations such as indoor dance events. We propose a new method for estimating crowd density by anonymous, non-participatory, indoor Wi-Fi loc...

    Authors: Sonja Georgievska, Philip Rutten, Jan Amoraal, Elena Ranguelova, Rena Bakhshi, Ben L. de Vries, Michael Lees and Sander Klous

    Citation: Journal of Big Data 2019 6:31

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Journal of Big Data Accepted into Scopus!

We are pleased to announce that the Journal of Big Data has been accepted into Scopus, the world's largest abstract and citation database of peer-reviewed literature. Read more about the journal's abstract and indexing on the 'About' page.

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