Web personalization issues in big data and Semantic Web: challenges andopportunities

Raufi, Bujar; Ismaili, Florije; Ajdari, Jaumin; Zenuni, Xhemal

doi:10.3906/elk-1812-25

Cited by 3 publications

(1 citation statement)

References 38 publications

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“…With the increase in the data volume of IoT equipment and the rapid increase in data volume transmitted through the network, the performance of cloud computing has gradually reached a bottleneck, and it cannot meet these requirements. Therefore, the existing research focuses on how to improve energy efficiency [18,19]. However, edge computing transfers computing power from the centralized cloud server to the node near the device end of the IoT, and realizes data preprocessing before entry to the cloud server [20].…”

Section: Edge Computing For the Iotmentioning

confidence: 99%

Sensor anomaly detection in the industrial internet of things based on edge computing

Kong¹,

Liu²,

Zhang³

et al. 2020

Turk J Elec Eng & Comp Sci

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In the industrial internet of things (IIoT), because thousands of pieces of hardware, instruments, and various controllers are involved, the core problem is the sensors. Detection using sensors is the bottom line of the IIoT, directly affecting the detection accuracy and control indicators of the IIoT system. However, when a large number of realtime data generated by IIoT devices are transferred to cloud computing centers, large-scale data will inevitably bring computing load, which will affect the computing speed of cloud computing centers and increase the computing load of cloud computing data centers. These factors directly lead to instability and delay in sensor data collected in real time in the IIoT. In this paper, a sensor outlier detection algorithm based on edge calculation is proposed. Firstly, focusing on the problem of the large amount of data in terminal equipment of the IIoT, the edge technology method of data compression is used to optimize the compression of sensor data, and different thresholds are set according to different industrial process requirements, so as to ensure the real-time aspect and authenticity of the data. Then, using the K-means clustering algorithm, the compressed test data sets are analyzed and the abnormal sensor detection values and labels are obtained. Finally, the effectiveness of such an approach is evaluated through a sample case study involving a temperature control system.

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Section: Edge Computing For the Iotmentioning

confidence: 99%

Sensor anomaly detection in the industrial internet of things based on edge computing

Kong¹,

Liu²,

Zhang³

et al. 2020

Turk J Elec Eng & Comp Sci

View full text Add to dashboard Cite

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Getting users out of the loop: Key factors to surpass the messy middle point

Nichifor

Brătucu

Chițu

et al. 2023

Electronic Commerce Research and Applications

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15 years of Big Data: a systematic literature review

Tosi,

Kokaj,

Roccetti

2024

J Big Data

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Big Data is still gaining attention as a fundamental building block of the Artificial Intelligence and Machine Learning world. Therefore, a lot of effort has been pushed into Big Data research in the last 15 years. The objective of this Systematic Literature Review is to summarize the current state of the art of the previous 15 years of research about Big Data by providing answers to a set of research questions related to the main application domains for Big Data analytics; the significant challenges and limitations researchers have encountered in Big Data analysis, and emerging research trends and future directions in Big Data. The review follows a predefined procedure that automatically searches five well-known digital libraries. After applying the selection criteria to the results, 189 primary studies were identified as relevant, of which 32 were Systematic Literature Reviews. Required information was extracted from the 32 studies and summarized. Our Systematic Literature Review sketched the picture of 15 years of research in Big Data, identifying application domains, challenges, and future directions in this research field. We believe that a substantial amount of work remains to be done to align and seamlessly integrate Big Data into data-driven advanced software solutions of the future.

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Web personalization issues in big data and Semantic Web: challenges andopportunities

Cited by 3 publications

References 38 publications

Sensor anomaly detection in the industrial internet of things based on edge computing

Sensor anomaly detection in the industrial internet of things based on edge computing

Getting users out of the loop: Key factors to surpass the messy middle point

15 years of Big Data: a systematic literature review

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