@inproceedings{ea2b5c9e4f2a49c5838130c42ac2cda7,
title = "Data mining applied to oil well using K-Means and DBSCAN",
abstract = "Oil is essential to our life mainly in transportation, and thus the productivity of oil well is very important. Classification of oil wells can make it easier to manage wells to ensure good oil productivity. Machine learning is an emerging technology of analyzing data in which cluster is a good way to do classification. The paper will apply two kinds of cluster method to the data from Dagang oil well and then do analysis on not only the classification results but also the choice of method for future analysis.",
keywords = "DBSCAN, K-means, PCA, cluster, oil well",
author = "Chang Lu and Yueting Shi and Yueyang Chen and Shiqi Bao and Lixing Tang",
note = "Publisher Copyright: {\textcopyright} 2016 IEEE.; 7th International Conference on Cloud Computing and Big Data, CCBD 2016 ; Conference date: 16-11-2016 Through 18-11-2016",
year = "2017",
month = jul,
day = "13",
doi = "10.1109/CCBD.2016.018",
language = "English",
series = "Proceedings - 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "37--40",
booktitle = "Proceedings - 2016 7th International Conference on Cloud Computing and Big Data, CCBD 2016",
address = "United States",
}