@inproceedings{c1bedfa0ef184b3f8c2afa50a16de3b4,
title = "Research on knowledge mining for agricultural machinery maintenance based on association rules",
abstract = "To solve the reusing and sharing problems of fault knowledge which is short of fault knowledge base, research of knowledge representation and knowledge discovery method of agricultural machinery with the maintenance support to knowledge discovery and reuse purpose was carried out. With Chinese segmentation tools, information extraction technologies of Chinese fields in agricultural machinery fault data were studied. Research of data mining technology about mining implicit relevance information from fault data for founding of agricultural fault knowledge base by association rules algorithm was studied. This method was proved feasible to build agricultural machinery maintenance fault knowledge base by dealing with the real data.",
keywords = "association rules, knowledge discovery, maintenance, segmentation",
author = "Yaoguang Hu and Zhengjie Guo and Jingqian Wen and Jialin Han",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015 ; Conference date: 15-06-2015 Through 17-06-2015",
year = "2015",
month = nov,
day = "20",
doi = "10.1109/ICIEA.2015.7334235",
language = "English",
series = "Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "885--890",
booktitle = "Proceedings of the 2015 10th IEEE Conference on Industrial Electronics and Applications, ICIEA 2015",
address = "United States",
}