Big Data Analytics and Intelligent Computation to Advance Novel Applications
This special issue belongs to the section "Internet of Things".
Special Issue Information
Dear Colleagues,
Big data analytics and intelligent computation are a hot topic to advance data-based services in real applications. However, most big data platforms, algorithms, and computational solutions are too general to be applied in novel application scenarios. For instance, in some sensor network applications, there are specific requirements regarding data analytics and computational resources. The sensor data volume is often huge and cannot fully be stored for processing. Sensor data are dynamic and updated over time, while sensor data are mostly consumed in streaming-style strategies. These specific requirements have become the key bottlenecks in utilizing the existing research outputs in big data analytics and intelligent computation. Therefore, to address these novel challenges, new technologies and feasible solutions of big data analytics and intelligent computation are now being pushed to a new frontier.
This Special Issue aims to establish an emerging forum and attract high-quality research submissions from worldwide scholars to develop novel data analytic models, efficient computing algorithms, deep learning solutions, as well as practical frameworks and systems. We also encourage authors to deploy the existing big data analytics solutions with a reasonable extension to adapt their appropriateness in novel application scenarios. The research findings will help industry practitioners and organizations to make smart decisions in real applications and reduce the computational cost.
Dr. Jianxin Li
Dr. Bin Wang
Dr. Jihong Park
Guest Editors
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Keywords
- fault-tolerant prediction models
- fault-tolerant recommendation models
- big data feature learning
- big-data-based energy management system and framework
- communication reduction in distributed environment
- novel applications of IoT devices
- novel framework evaluation and metric
- novel system evaluation and metric
- network data mining and clustering
- novel query types in streaming data
- noisy data cleaning
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Published Papers
Sensors - ISSN 1424-8220