Health Discourse Regarding Syrian Refugees in Türkiye on X (Formerly Twitter): Longitudinal Sentiment and Stance Analysis. [PDF]
Ataç Ö, Adeel AB, Ataç IE.
europepmc +1 more source
Data Mining and Network Pharmacology Characterize Medication Patterns of Chinese Herbal Medicine for Bovine Viral Diarrhea. [PDF]
An M +5 more
europepmc +1 more source
AI-Assisted Literature Mining Reveals Spatiotemporal Heterogeneity and Progression Trajectories of Traditional Chinese Medicine Syndromes in Coronary Heart Disease in China. [PDF]
Che Q +15 more
europepmc +1 more source
Study on urban residents' travel mode choice based on the CART-Apriori method. [PDF]
Song H, Wang X, Tian W, Shi L, Li S.
europepmc +1 more source
Temporal Drivers of Opioid-Related ED Visits: An Ensemble Machine Learning Study With Consensus-Based Feature Attribution. [PDF]
Dixon RJ, Price ET.
europepmc +1 more source
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Mining Skier Transportation Patterns From Ski Resort Lift Usage Data
IEEE Transactions on Human-Machine Systems, 2017Descriptive data analysis is used for mining spatial and temporal patterns from ski lift entrance data. The data, collected through radio-frequency identification scanners, cover one skiing season with approximately 1.2 million recorded ski lift transportations.
Zoran Obradovic +2 more
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On Asymptotic Distributions and Confidence Intervals for LIFT Measures in Data Mining
Journal of the American Statistical Association, 2015A LIFT measure, such as the response rate, lift, or the percentage of captured response, is a fundamental measure of effectiveness for a scoring rule obtained from data mining, which is estimated from a set of validation data. In this article, we study how to construct confidence intervals of the LIFT measures.
Wenxin Jiang
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Integrating Data Mining and Expert Knowledge for an Artificial-Lift Advisory System
Journal of Petroleum Technology, 2010This article, written by Assistant Technology Editor Karen Bybee, contains highlights of paper SPE 128636, ’Integrat ing Data Mining and Expert Knowledge for an Artificial Lift Advisory System,’ by E. De la Vega, G. Sandoval, and M. Garcia, SPE, Pemex, and G. Nunez, SPE, A. Al-Kinani, SPE, R.W. Holy, SPE, H. Escalona, SPE, and M.
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