The Review of Socionetwork Strategies
The Review of Socionetwork Strategies promotes data mining and data analysis for business and the economy through interdisciplinary research between computer science and the social sciences. The Review welcomes articles such as those dealing with business, economic and statistical analyses related to large-scale networks, and to huge amounts of data. The focus of The Review of Socionetwork Strategies is on empirical findings, methodologies, and theoretical and conceptual insights across areas of research in policy and in advanced information technology such as cloud computing, data mining, and multi-agent simulation. Areas of interest include, but are not limited to, consumer behavior, corporate strategy, industrial organization, and government policy in the fields of finance, medicine, nursing care, and retail, for example.
This Journal is supported by Kansai University and Matching Fund Subsidy from MEXT (Ministry of Education, Culture, Sports, Science and Technology).
Yasuharu Ukai (December 2016)
Principal Component Selection for Neural Network Classification of Active Ingredients from Near Infrared Spectra
Nigel Yee (December 2016)
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