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Page 11 of 13

  1. Complications of pregnancy and childbirth are a leading cause of maternal morbidities and mortalities in developing countries. World Health Organization (WHO) estimates that over 500,000 women and girls die ea...

    Authors: Mekuanint Simeneh Workie and Ayenew Molla Lakew
    Citation: Journal of Big Data 2018 5:7
  2. 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...

    Authors: Georgios Chatzigeorgakidis, Sophia Karagiorgou, Spiros Athanasiou and Spiros Skiadopoulos
    Citation: Journal of Big Data 2018 5:4
  3. 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...

    Authors: Sahar Sohangir, Dingding Wang, Anna Pomeranets and Taghi M. Khoshgoftaar
    Citation: Journal of Big Data 2018 5:3
  4. 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...

    Authors: Karim Abouelmehdi, Abderrahim Beni-Hessane and Hayat Khaloufi
    Citation: Journal of Big Data 2018 5:1
  5. The huge variety of NoSQL Big Data has tossed a need for new pathways to store, process and analyze it. The quantum of data created is inconceivable along with a mixed breath of unknown veracity and creative v...

    Authors: Sachin S. Patil and Shefali P. Sonavane
    Citation: Journal of Big Data 2017 4:49
  6. 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...

    Authors: Luca Venturini, Elena Baralis and Paolo Garza
    Citation: Journal of Big Data 2017 4:44
  7. 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...

    Authors: Nilay Khare, Alind Khare and Farhan Khan
    Citation: Journal of Big Data 2017 4:41
  8. 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...

    Authors: M. V. Sangameswar, M. Nagabhushana Rao and S. Satyanarayana
    Citation: Journal of Big Data 2017 4:39
  9. Data sensing, information processing, and networking technologies are being fast embedded into the very fabric of the contemporary city to enable the use of innovative solutions to overcome the challenges of s...

    Authors: Simon Elias Bibri and John Krogstie
    Citation: Journal of Big Data 2017 4:38
  10. Big datasets are often stored in flat files and can contain contradictory data. Contradictory data undermines the soundness of the information from a noisy dataset. Traditional tools such as pie chart and bar ...

    Authors: Honour Chika Nwagwu, George Okereke and Chukwuemeka Nwobodo
    Citation: Journal of Big Data 2017 4:36
  11. This paper proposes a reinforcement learning based message transfer model for transferring news report messages through a selected path in a trusted provenance network with the objective of maximizing the rewa...

    Authors: Sanjoy Kumar Mukherjee and Sivaji Bandyopadhyay
    Citation: Journal of Big Data 2017 4:35
  12. Classifying short texts to one category or clustering semantically related texts is challenging, and the importance of both is growing due to the rise of microblogging platforms, digital news feeds, and the li...

    Authors: Justin Zhan and Binay Dahal
    Citation: Journal of Big Data 2017 4:34
  13. The restrictions that are related to using single distribution resampling for some specific computing devices’ memory gives developers several difficulties as a result of the increased effort and time needed ...

    Authors: Wan Mohd Yaakob Wan Bejuri, Mohd Murtadha Mohamad, Raja Zahilah Raja Mohd Radzi, Mazleena Salleh and Ahmad Fadhil Yusof
    Citation: Journal of Big Data 2017 4:33
  14. The recent technology development in the concern of microarray experiments has provided many new potentialities in terms of simultaneous measurement. But new challenges have arisen from these massive quantitie...

    Authors: Fadoua Badaoui, Amine Amar, Laila Ait Hassou, Abdelhak Zoglat and Cyrille Guei Okou
    Citation: Journal of Big Data 2017 4:32
  15. Predicting stock market price is considered as a challenging task of financial time series analysis, which is of great interest to stock investors, stock traders and applied researchers. Many machine learning ...

    Authors: Meryem Ouahilal, Mohammed El Mohajir, Mohamed Chahhou and Badr Eddine El Mohajir
    Citation: Journal of Big Data 2017 4:31
  16. The explosive growing number of data from mobile devices, social media, Internet of Things and other applications has highlighted the emergence of big data. This paper aims to determine the worldwide research ...

    Authors: Ali Kalantari, Amirrudin Kamsin, Halim Shukri Kamaruddin, Nader Ale Ebrahim, Abdullah Gani, Ali Ebrahimi and Shahaboddin Shamshirband
    Citation: Journal of Big Data 2017 4:30
  17. Transfer learning has been demonstrated to be effective for many real-world applications as it exploits knowledge present in labeled training data from a source domain to enhance a model’s performance in a tar...

    Authors: Oscar Day and Taghi M. Khoshgoftaar
    Citation: Journal of Big Data 2017 4:29
  18. Big data has become popular for processing, storing and managing massive volumes of data. The clustering of datasets has become a challenging issue in the field of big data analytics. The K-means algorithm is ...

    Authors: Chowdam Sreedhar, Nagulapally Kasiviswanath and Pakanti Chenna Reddy
    Citation: Journal of Big Data 2017 4:27
  19. Predictive analytics has gained a lot of reputation in the emerging technology Big data. Predictive analytics is an advanced form of analytics. Predictive analytics goes beyond data mining. A huge amount of me...

    Authors: N. Jayanthi, B. Vijaya Babu and N. Sambasiva Rao
    Citation: Journal of Big Data 2017 4:26
  20. Text similarity measurement aims to find the commonality existing among text documents, which is fundamental to most information extraction, information retrieval, and text mining problems. Cosine similarity b...

    Authors: Sahar Sohangir and Dingding Wang
    Citation: Journal of Big Data 2017 4:25
  21. With the increasing demand for examining and extracting patterns from massive amounts of data, it is critical to be able to train large models to fulfill the needs that recent advances in the machine learning ...

    Authors: Maryam M. Najafabadi, Taghi M. Khoshgoftaar, Flavio Villanustre and John Holt
    Citation: Journal of Big Data 2017 4:22
  22. Determining user’s perception of a brand in short periods of time has become crucial for business. Distilling brand perception directly from people’s comments in social media has promise. Current techniques fo...

    Authors: Manu Shukla, Raimundo Dos Santos, Andrew Fong and Chang-Tien Lu
    Citation: Journal of Big Data 2017 4:17
  23. Detecting botnets in a network is crucial because bots impact numerous areas such as cyber security, finance, health care, law enforcement, and more. Botnets are becoming more sophisticated and dangerous day-b...

    Authors: Sudipta Chowdhury, Mojtaba Khanzadeh, Ravi Akula, Fangyan Zhang, Song Zhang, Hugh Medal, Mohammad Marufuzzaman and Linkan Bian
    Citation: Journal of Big Data 2017 4:14
  24. The ability to process large volumes of data on the fly, as soon as they become available, is a fundamental requirement in today’s information systems. Modern distributed stream processing engines (SPEs) addre...

    Authors: Lorenzo Affetti, Riccardo Tommasini, Alessandro Margara, Gianpaolo Cugola and Emanuele Della Valle
    Citation: Journal of Big Data 2017 4:12
  25. Cloud data stores that can handle very large amounts of data, such as Apache HBase, have accelerated the use of non-relational databases (coined as NoSQL databases) as a way of addressing RDB database limitati...

    Authors: R. Ouanouki, A. April, A. Abran, A. Gomez and J. M. Desharnais
    Citation: Journal of Big Data 2017 4:10
  26. Proliferation of structural, semi-structural and no-structural data, has challenged the scalability, flexibility and processability of the traditional relational database management systems (RDBMS). The next g...

    Authors: Nadeem Qaisar Mehmood, Rosario Culmone and Leonardo Mostarda
    Citation: Journal of Big Data 2017 4:8

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