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  1. Big Data analytics for storing, processing, and analyzing large-scale datasets has become an essential tool for the industry. The advent of distributed computing frameworks such as Hadoop and Spark offers effi...

    Authors: N. Ahmed, Andre L. C. Barczak, Teo Susnjak and Mohammed A. Rashid
    Citation: Journal of Big Data 2020 7:110
  2. Natural language processing has witnessed remarkable progress with the advent of deep learning techniques. Text summarization, along other tasks like text translation and sentiment analysis, used deep neural n...

    Authors: Molham Al-Maleh and Said Desouki
    Citation: Journal of Big Data 2020 7:109

    The Correction to this article has been published in Journal of Big Data 2021 8:56

  3. A massive amount of data is generated with the evolution of modern technologies. This high-throughput data generation results in Big Data, which consist of many features (attributes). However, irrelevant featu...

    Authors: A. N. M. Bazlur Rashid, Mohiuddin Ahmed, Leslie F. Sikos and Paul Haskell-Dowland
    Citation: Journal of Big Data 2020 7:107

    The Correction to this article has been published in Journal of Big Data 2020 7:111

  4. Flight delay is inevitable and it plays an important role in both profits and loss of the airlines. An accurate estimation of flight delay is critical for airlines because the results can be applied to increas...

    Authors: Maryam Farshchian Yazdi, Seyed Reza Kamel, Seyyed Javad Mahdavi Chabok and Maryam Kheirabadi
    Citation: Journal of Big Data 2020 7:106
  5. The amount of data produced by sensors, social and digital media, and Internet of Things (IoTs) are rapidly increasing each day. Decision makers often need to sift through a sea of Big Data to utilize informat...

    Authors: Tian J. Ma, Rudy J. Garcia, Forest Danford, Laura Patrizi, Jennifer Galasso and Jason Loyd
    Citation: Journal of Big Data 2020 7:103
  6. There has been growing demand for 3D modeling from earth observations, especially for purposes of urban and regional planning and management. The results of 3D observations has slowly become the primary source...

    Authors: Ahmad Gamal, Ari Wibisono, Satrio Bagus Wicaksono, Muhammad Alvin Abyan, Nur Hamid, Hanif Arif Wisesa, Wisnu Jatmiko and Ronny Ardhianto
    Citation: Journal of Big Data 2020 7:102
  7. Sorting algorithms are among the most commonly used algorithms in computer science and modern software. Having efficient implementation of sorting is necessary for a wide spectrum of scientific applications. T...

    Authors: Marek Nowicki
    Citation: Journal of Big Data 2020 7:101
  8. In recent years, deep learning has become one of the most important topics in computer sciences. Deep learning is a growing trend in the edge of technology and its applications are now seen in many aspects of ...

    Authors: Hamidreza Bolhasani and Somayyeh Jafarali Jassbi
    Citation: Journal of Big Data 2020 7:100
  9. Object detection and gender recognition were two different categories to be classified in a single section is a complicated task and this approach helps in supporting the blind people for an artificial vision....

    Authors: Damodara Krishna Kishore Galla, Babu Reddy Mukamalla and Rama Prakasha Reddy Chegireddy
    Citation: Journal of Big Data 2020 7:98
  10. In the light of the recent technological advances in computing and data explosion, the complex interactions of the Sustainable Development Goals (SDG) present both a challenge and an opportunity to researchers...

    Authors: Kassim S. Mwitondi, Isaac Munyakazi and Barnabas N. Gatsheni
    Citation: Journal of Big Data 2020 7:97
  11. A Full Blood Count (FBC) is a common blood test including 20 parameters, such as haemoglobin and platelets. FBCs from Electronic Health Record (EHR) databases provide a large sample of anonymised individual pa...

    Authors: Pradeep S. Virdee, Alice Fuller, Michael Jacobs, Tim Holt and Jacqueline Birks
    Citation: Journal of Big Data 2020 7:96
  12. Gradient Boosted Decision Trees (GBDT’s) are a powerful tool for classification and regression tasks in Big Data. Researchers should be familiar with the strengths and weaknesses of current implementations of ...

    Authors: John T. Hancock and Taghi M. Khoshgoftaar
    Citation: Journal of Big Data 2020 7:94
  13. A modern urban infrastructure no longer operates in isolation, but instead, leverages the latest technologies to collect, process, and distribute aggregated knowledge in order to improve the quality of the pro...

    Authors: Nataliia Neshenko, Christelle Nader, Elias Bou-Harb and Borko Furht
    Citation: Journal of Big Data 2020 7:92
  14. Argumentation mining is a research field which focuses on sentences in type of argumentation. Argumentative sentences are often used in daily communication and have important role in each decision or conclusio...

    Authors: Derwin Suhartono, Aryo Pradipta Gema, Suhendro Winton, Theodorus David, Mohamad Ivan Fanany and Aniati Murni Arymurthy
    Citation: Journal of Big Data 2020 7:90
  15. Significant investments to upgrade and construct large-scale scientific facilities demand commensurate investments in R&D to design algorithms and computing approaches to enable scientific and engineering brea...

    Authors: E. A. Huerta, Asad Khan, Edward Davis, Colleen Bushell, William D. Gropp, Daniel S. Katz, Volodymyr Kindratenko, Seid Koric, William T. C. Kramer, Brendan McGinty, Kenton McHenry and Aaron Saxton
    Citation: Journal of Big Data 2020 7:88
  16. This paper describes a method for learning anomaly behavior in the video by finding an attention region from spatiotemporal information, in contrast to the full-frame learning. In our proposed method, a robust...

    Authors: Nasaruddin Nasaruddin, Kahlil Muchtar, Afdhal Afdhal and Alvin Prayuda Juniarta Dwiyantoro
    Citation: Journal of Big Data 2020 7:87
  17. Real-time information mining of a big dataset consisting of time series data is a very challenging task. For this purpose, we propose using the mean distance and the standard deviation to enhance the accuracy ...

    Authors: Ari Wibisono, Petrus Mursanto, Jihan Adibah, Wendy D. W. T. Bayu, May Iffah Rizki, Lintang Matahari Hasani and Valian Fil Ahli
    Citation: Journal of Big Data 2020 7:85
  18. This study deals with the problem of rea-time obtaining quality data on the road traffic parameters based on the static street video surveillance camera data. The existing road traffic monitoring solutions are...

    Authors: Kirill Khazukov, Vladimir Shepelev, Tatiana Karpeta, Salavat Shabiev, Ivan Slobodin, Irakli Charbadze and Irina Alferova
    Citation: Journal of Big Data 2020 7:84
  19. Extensive usage of Internet based applications in day to day life has led to generation of huge amounts of data every minute. Apart from humans, data is generated by machines like sensors, satellite, CCTV etc....

    Authors: Gousiya Begum, S. Zahoor Ul Huq and A. P. Siva Kumar
    Citation: Journal of Big Data 2020 7:82
  20. The growing number of Internet of Things (IoT) devices provide a massive pool of sensing data. However, turning data into actionable insights is not a trivial task, especially in the context of IoT, where appl...

    Authors: Tanmaya Mahapatra
    Citation: Journal of Big Data 2020 7:81
  21. During the last decade, the use of online search traffic data is becoming popular in examining, analyzing, and predicting human behavior, with Google Trends being a popular tool in monitoring and analyzing the...

    Authors: Amaryllis Mavragani, Konstantinos Gkillas and Konstantinos P. Tsagarakis
    Citation: Journal of Big Data 2020 7:79
  22. Big graphs are part of the movement of “Not Only SQL” databases (also called NoSQL) focusing on the relationships between data, rather than the values themselves. The data is stored in vertices while the edges...

    Authors: Wilfried Yves Hamilton Adoni, Tarik Nahhal, Moez Krichen, Abdeltif El byed and Ismail Assayad
    Citation: Journal of Big Data 2020 7:76
  23. This research proposes a system based on a combination of various components for parallel modelling and forecasting the processes in networks with data assimilation from the real network. The main novelty of t...

    Authors: Oksana Severiukhina, Sergey Kesarev, Klavdiya Bochenina, Alexander Boukhanovsky, Michael H. Lees and Peter M. A. Sloot
    Citation: Journal of Big Data 2020 7:72
  24. Urban transport investments have contributed to the exponential increase of value from land and properties around the built infrastructure. Although literature had shown evidence of value uplift from the resid...

    Authors: Mohammed Ali Berawi, Perdana Miraj, Gunawan Saroji and Mustika Sari
    Citation: Journal of Big Data 2020 7:71
  25. Since canonical machine learning algorithms assume that the dataset has equal number of samples in each class, binary classification became a very challenging task to discriminate the minority class samples ef...

    Authors: Jafar Tanha, Yousef Abdi, Negin Samadi, Nazila Razzaghi and Mohammad Asadpour
    Citation: Journal of Big Data 2020 7:70
  26. Traditional food knowledge (TFK) is an essential aspect of human life. In terms of sociocultural aspects, TFK is necessary to protect ancestral culture. In terms of health, traditional foods contain better and...

    Authors: Ari Wibisono, Hanif Arief Wisesa, Zulia Putri Rahmadhani, Puteri Khatya Fahira, Petrus Mursanto and Wisnu Jatmiko
    Citation: Journal of Big Data 2020 7:69
  27. Prediction using machine learning algorithms is not well adapted in many parts of the business decision processes due to the lack of clarity and flexibility. The erroneous data as inputs in the prediction proc...

    Authors: Samiul Islam and Saman Hassanzadeh Amin
    Citation: Journal of Big Data 2020 7:65
  28. Fiber optics cable has been adopted by telecommunication companies worldwide as the primary medium of transmission. The cable is steadily replacing long-haul microwave, copper cable, and satellite transmission...

    Authors: Owusu Nyarko-Boateng, Adebayo Felix Adekoya and Benjamin Asubam Weyori
    Citation: Journal of Big Data 2020 7:64
  29. Contraction Clustering (RASTER) is a single-pass algorithm for density-based clustering of 2D data. It can process arbitrary amounts of data in linear time and in constant memory, quickly identifying approxima...

    Authors: Gregor Ulm, Simon Smith, Adrian Nilsson, Emil Gustavsson and Mats Jirstrand
    Citation: Journal of Big Data 2020 7:62

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    5.095 - SNIP (Source Normalized Impact per Paper)
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