Machine Learning for Business Analytics: Case Studies and Open Research Problems
Studies in Computational Intelligence, ISSN: 1860-9503, Vol: 1006, Page: 1-26
2022
- 1Citations
- 6Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Book Chapter Description
Business analytics (BA) refers to the process of organizing, processing, and examining business data for the purpose of gaining useful information that can be used to resolve problems and enhance the efficiency, productivity, and revenue. Applications of machine learning (ML) within BA have proliferated in recent years and have revolutionized the process of business decision-making, despite concerns that implementation of BA functions could lead to job loss. This chapter describes the different ML techniques being currently used in business. Several case studies in which ML is used for business purposes are presented. Open research problems in the areas of ML in BA are discussed.
Bibliographic Details
http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85127862833&origin=inward; http://dx.doi.org/10.1007/978-3-030-92245-0_1; https://link.springer.com/10.1007/978-3-030-92245-0_1; https://dx.doi.org/10.1007/978-3-030-92245-0_1; https://link.springer.com/chapter/10.1007/978-3-030-92245-0_1
Springer Science and Business Media LLC
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