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  1. Content type: Research

    One of the most common diseases among women is breast cancer, the early diagnosis of which is of paramount importance. Given the time-consuming nature of the diagnosis process of the disease, using new methods...

    Authors: Seyed Reza Kamel, Reyhaneh YaghoubZadeh and Maryam Kheirabadi

    Citation: Journal of Big Data 2019 6:90

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  2. Content type: Research

    With the growing use of information technology in all life domains, hacking has become more negatively effective than ever before. Also with developing technologies, attacks numbers are growing exponentially e...

    Authors: Khloud Al Jallad, Mohamad Aljnidi and Mohammad Said Desouki

    Citation: Journal of Big Data 2019 6:88

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  3. Content type: Research

    The trend of current software inevitably leads to the big data era. There are much of large software developed from hundreds to thousands of modules. In software development projects, finding the defect pronen...

    Authors: Aris Marjuni, Teguh B. Adji and Ridi Ferdiana

    Citation: Journal of Big Data 2019 6:87

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  4. Content type: Research

    With the popularity of e-commerce, posting online product reviews expressing customer’s sentiment or opinion towards products has grown exponentially. Sentiment analysis is a computational method that plays an...

    Authors: Bagus Setya Rintyarna, Riyanarto Sarno and Chastine Fatichah

    Citation: Journal of Big Data 2019 6:84

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  5. Content type: Research

    As social network structures evolve constantly, it is necessary to design an efficient mechanism to track the influential nodes and accurate communities in the networks. The attributed graph represents the inf...

    Authors: Sanket Chobe and Justin Zhan

    Citation: Journal of Big Data 2019 6:83

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  6. Content type: Survey Paper

    In the era of accelerating growth of genomic data, feature-selection techniques are believed to become a game changer that can help substantially reduce the complexity of the data, thus making it easier to ana...

    Authors: Khawla Tadist, Said Najah, Nikola S. Nikolov, Fatiha Mrabti and Azeddine Zahi

    Citation: Journal of Big Data 2019 6:79

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  7. 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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  8. 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

  9. 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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  10. 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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  11. 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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  12. 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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  13. 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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  14. 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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  15. 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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  16. 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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  17. 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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  18. 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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  19. 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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  20. 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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  21. 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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  22. 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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  23. 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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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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