Journal of Big Data
SCOPUS (2014-2025)SCIE-ISI
2196-1115
Cơ quản chủ quản: Springer Nature , SpringerOpen
Lĩnh vực:
Hardware and ArchitectureInformation SystemsInformation Systems and ManagementComputer Networks and Communications
Phân tích ảnh hưởng
Các bài báo tiêu biểu
Internet of Things is a revolutionary approach for future technology enhancement: a review
Tập 6 Số 1 - 2019
AbstractInternet of Things (IoT) is a new paradigm that has changed the
traditional way of living into a high tech life style. Smart city, smart homes,
pollution control, energy saving, smart transportation, smart industries are
such transformations due to IoT. A lot of crucial research studies and
investigations have been done in order to enhance the technology through IoT.
However, there are sti...
CatBoost for big data: an interdisciplinary review
- 2020
AbstractGradient 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 GBDT’s in order
to use them effectively and make successful contributions. CatBoost is a member
of the family of GBDT machine learning ensemble techniques. Since its debut in
late 201...
An industrial big data pipeline for data-driven analytics maintenance applications in large-scale smart manufacturing facilities
Tập 2 Số 1 - 2015
A review of data mining using big data in health informatics
- 2014
Abstract The amount of data produced within Health Informatics has grown to be
quite vast, and analysis of this Big Data grants potentially limitless
possibilities for knowledge to be gained. In addition, this information can
improve the quality of healthcare offered to patients. However, there are a
number of issues that arise when dealing with these vast quantities of data,
especially how to ana...
Enlarging smaller images before inputting into convolutional neural network: zero-padding vs. interpolation
Tập 6 Số 1 - 2019
AbstractThe input to a machine learning model is a one-dimensional feature
vector. However, in recent learning models, such as convolutional and recurrent
neural networks, two- and three-dimensional feature tensors can also be inputted
to the model. During training, the machine adjusts its internal parameters to
project each feature tensor close to its target. After training, the machine can
be us...
A survey and analysis of intrusion detection models based on CSE-CIC-IDS2018 Big Data
- 2020
AbstractThe exponential growth in computer networks and network applications
worldwide has been matched by a surge in cyberattacks. For this reason, datasets
such as CSE-CIC-IDS2018 were created to train predictive models on network-based
intrusion detection. These datasets are not meant to serve as repositories for
signature-based detection systems, but rather to promote research on
anomaly-based...