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Research Advising System Based on Prescriptive Analytics

2014; Springer Science+Business Media; Linguagem: Inglês

10.1007/978-3-642-55038-6_89

1876-1119

Sa-Kwang Song, Do-Heon Jeong, Jinhyung Kim, Myunggwon Hwang, Jangwon Gim, Hanming Jung,

Big Data and Business Intelligence

As the amount of data increases enormously, business analytics such as descriptive, predictive, and prescriptive analytics is one of the most important topics for better decision making especially for CTO or CIO in corporate. Prescriptive analytics shows fundamental difference with descriptive analytics and predictive analytics in that it requires high-value alternative actions or decisions to achieve a given goal. However, only a few studies have been introduced since it is a emerging technology. Thus, this study aims to trigger research on this technical area by implementing a prescriptive analytics system and by verifying it in the point of usability and usefulness. The system, InSciTe Advisory, is focused on improving research performance and is based on 5W1H questions to build actionable strategies to achieve a given goal. The comparison evaluation of the system with Elsevier SciVal showed a rate of 118.8% in usefulness and reliability.