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  1. Methodology

    A novel adaptable approach for sentiment analysis on big social data

    Gathering public opinion by analyzing big social data has attracted wide attention due to its interactive and real time nature. For this, recent studies have relied on both social media and sentiment analysis ...

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

    Journal of Big Data 2018 5:12

    Published on: 8 March 2018

  2. Research

    Concept and benchmark results for Big Data energy forecasting based on Apache Spark

    The present article describes a concept for the creation and application of energy forecasting models in a distributed environment. Additionally, a benchmark comparing the time required for the training and ap...

    Jorge Ángel González Ordiano, Andreas Bartschat, Nicole Ludwig, Eric Braun, Simon Waczowicz, Nicolas Renkamp, Nico Peter, Clemens Düpmeier, Ralf Mikut and Veit Hagenmeyer

    Journal of Big Data 2018 5:11

    Published on: 6 March 2018

  3. Research

    GraphZIP: a clique-based sparse graph compression method

    Massive graphs are ubiquitous and at the heart of many real-world problems and applications ranging from the World Wide Web to social networks. As a result, techniques for compressing graphs have become increa...

    Ryan A. Rossi and Rong Zhou

    Journal of Big Data 2018 5:10

    Published on: 3 March 2018

  4. Research

    Who is behind the wheel? Driver identification and fingerprinting

    In the last decade, significant advances have been made in sensing and communication technologies. Such progress led to a considerable growth in the development and use of intelligent transportation systems. C...

    Saad Ezzini, Ismail Berrada and Mounir Ghogho

    Journal of Big Data 2018 5:9

    Published on: 27 February 2018

  5. Methodology

    StreamAligner: a streaming based sequence aligner on Apache Spark

    Next-Generation Sequencing technologies are generating a huge amount of genetic data that need to be mapped and analyzed. Single machine sequence alignment tools are becoming incapable or inefficient in keepin...

    Sanjay Rathee and Arti Kashyap

    Journal of Big Data 2018 5:8

    Published on: 27 February 2018

  6. Research

    FML-kNN: scalable machine learning on Big Data using k-nearest neighbor joins

    Efficient management and analysis of large volumes of data is a demanding task of increasing scientific and industrial importance, as the ubiquitous generation of information governs more and more aspects of h...

    Georgios Chatzigeorgakidis, Sophia Karagiorgou, Spiros Athanasiou and Spiros Skiadopoulos

    Journal of Big Data 2018 5:4

    Published on: 6 February 2018

  7. Research

    Big Data: Deep Learning for financial sentiment analysis

    Deep Learning and Big Data analytics are two focal points of data science. Deep Learning models have achieved remarkable results in speech recognition and computer vision in recent years. Big Data is important...

    Sahar Sohangir, Dingding Wang, Anna Pomeranets and Taghi M. Khoshgoftaar

    Journal of Big Data 2018 5:3

    Published on: 25 January 2018

  8. Survey Paper

    Big healthcare data: preserving security and privacy

    Big data has fundamentally changed the way organizations manage, analyze and leverage data in any industry. One of the most promising fields where big data can be applied to make a change is healthcare. Big he...

    Karim Abouelmehdi, Abderrahim Beni-Hessane and Hayat Khaloufi

    Journal of Big Data 2018 5:1

    Published on: 9 January 2018

  9. Short report

    Some dimension reduction strategies for the analysis of survey data

    In the era of big data, researchers interested in developing statistical models are challenged with how to achieve parsimony. Usually, some sort of dimension reduction strategy is employed. Classic strategies are...

    Jiaying Weng and Derek S. Young

    Journal of Big Data 2017 4:43

    Published on: 8 December 2017

  10. Research

    Scaling associative classification for very large datasets

    Supervised learning algorithms are nowadays successfully scaling up to datasets that are very large in volume, leveraging the potential of in-memory cluster-computing Big Data frameworks. Still, massive datase...

    Luca Venturini, Elena Baralis and Paolo Garza

    Journal of Big Data 2017 4:44

    Published on: 8 December 2017

  11. Research

    HCudaBLAST: an implementation of BLAST on Hadoop and Cuda

    The world of DNA sequencing has not only been a difficult field since it was first worked upon, but it is also growing at an exponential rate. The amount of data involved in DNA searching is huge, thereby norm...

    Nilay Khare, Alind Khare and Farhan Khan

    Journal of Big Data 2017 4:41

    Published on: 16 November 2017

  12. Methodology

    Understanding deep learning via backtracking and deconvolution

    Convolutional neural networks are widely adopted for solving problems in image classification. In this work, we aim to gain a better understanding of deep learning through exploring the miss-classified cases i...

    Xing Fang

    Journal of Big Data 2017 4:40

    Published on: 13 November 2017

  13. Research

    An algorithm for identification of natural disaster affected area

    An important source of information presently is social media, which reports any major event including natural disasters. Social media also includes conversational data. As a result, the volume of data on socia...

    M. V. Sangameswar, M. Nagabhushana Rao and S. Satyanarayana

    Journal of Big Data 2017 4:39

    Published on: 7 November 2017

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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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