Name
Title | ||
|---|---|---|
Context-Aware Data Mining: Embedding External Data Sources In A Machine Learning Process |
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/978-3-319-59650-1_35 | HYBRID ARTIFICIAL INTELLIGENT SYSTEMS, HAIS 2017 |
Keywords | Field | DocType |
Context-aware data mining, Internet of things, Ambience intelligence | Data mining,Data stream mining,Embedding,Pattern recognition,Active learning (machine learning),Computer science,Internet of Things,Artificial intelligence,Machine learning | Conference |
Volume | ISSN | Citations |
10334 | 0302-9743 | 0 |
PageRank | References | Authors |
0.34 | 6 | 5 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Oliviu Matei | 1 | 43 | 11.15 |
| Teodor Rusu | 2 | 0 | 0.34 |
| Andrei Bozga | 3 | 0 | 0.34 |
| Petrica Pop Sitar | 4 | 0 | 0.68 |
| Carmen Anton | 5 | 0 | 0.68 |