Context-Aware Data Mining: Embedding External Data Sources in a Machine Learning Process

被引：11
|
作者：
Matei, Oliviu [1 ,3 ]
Rusu, Teodor [2 ]
Bozga, Andrei [1 ]
Pop-Sitar, Petrica [3 ]
Anton, Carmen [3 ]
机构：
[1] Holisun Srl, Baia Mare, Romania
[2] Univ Agr Sci & Vet Med, Cluj Napoca, Romania
[3] Tech Univ Cluj Napoca, North Univ Ctr Baia Mare, Cluj Napoca, Romania
来源：
HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2017 | 2017年 / 10334卷
关键词：
Context-aware data mining; Internet of things; Ambience intelligence; PREDICTION; FRAMEWORK;
D O I：
10.1007/978-3-319-59650-1_35
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
The article presents a data mining system capable of predicting the soil moisture using local data, provided by weather stations in real time, as well as context-related, publicly available data from web portals. We have proven that the quality and quantity of context data is very important for improving the accuracy of the predictions, comparing with classical scenario, in which only the local data is used.
引用
收藏
页码：415 / 426
页数：12
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