Mining Outlier Data in Mobile Internet-Based Large Real-Time Databases
Mining outlier data guarantees access security and data scheduling of parallel databases and maintains high-performance operation of real-time databases. Traditional mining methods generate abundant interference data with reduced accuracy, efficiency, and stability, causing severe deficiencies. This...
Saved in:
Main Authors: | Xin Liu, Yanju Zhou, Xiaohong Chen |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2018-01-01
|
Series: | Complexity |
Online Access: | http://dx.doi.org/10.1155/2018/9702304 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Large-Scale Real-Time Semantic Processing Framework for Internet of Things
by: Xi Chen, et al.
Published: (2015-10-01) -
Cloud Platform Based on Mobile Internet Service Opportunistic Drive and Application Aware Data Mining
by: Ge Zhou
Published: (2015-01-01) -
A Robust Skewed Boxplot for Detecting Outliers in Rainfall Observations in Real-Time Flood Forecasting
by: Chao Zhao, et al.
Published: (2019-01-01) -
In silico data mining of large-scale databases for the virtual screening of human interleukin-2 inhibitors
by: Halim Sobia Ahsan, et al.
Published: (2021-03-01) -
Nutrient composition databases in the age of big data: foodDB, a comprehensive, real-time database infrastructure
by: Peter Scarborough, et al.
Published: (2019-06-01)