通过使用社交网络挖掘,发现患者危险的自我用药方法

R. Samizadeh, M. K. Zadeh, Mahsa Jadidi, M. Rezapour, S. Vatankhah
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Discovery of dangerous self-medication methods with patients, by using social network mining
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来源期刊
International Journal of Business Intelligence and Data Mining
International Journal of Business Intelligence and Data Mining Decision Sciences-Statistics, Probability and Uncertainty
CiteScore
1.50
自引率
0.00%
发文量
89
期刊介绍: IJBIDM provides a forum for state-of-the-art developments and research as well as current innovative activities in business intelligence, data analysis and mining. Intelligent data analysis provides powerful and effective tools for problem solving in a variety of business modelling tasks. IJBIDM highlights intelligent techniques used for business modelling, including all areas of data visualisation, data pre-processing (fusion, editing, transformation, filtering, sampling), data engineering, data mining techniques, tools and applications, neurocomputing, evolutionary computing, fuzzy techniques, expert systems, knowledge filtering, and post-processing. Topics covered include Data extraction/reporting/cleaning/pre-processing OLAP, decision analysis, causal modelling Reasoning under uncertainty, noise in data Business intelligence cycle Model specification/selection/estimation Web technology, mining, agents Fuzzy, neural, evolutionary approaches Genetic algorithms, machine learning, expert/hybrid systems Bayesian inference, bootstrap, randomisation Exploratory/automated data analysis Knowledge-based analysis, statistical pattern recognition Data mining algorithms/processes Classification, projection, regression, optimisation clustering Information extraction/retrieval, human-computer interaction Multivariate data visualisation, tools.
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