Abstract:
Today's social informatics is facing the challenge of exponentially increasing data present online. However this massive amount of data is available across several hetero...Show MoreMetadata
Abstract:
Today's social informatics is facing the challenge of exponentially increasing data present online. However this massive amount of data is available across several heterogeneous platform making it a challenging task especially to comprehend useful information and effectively use it for business intelligence. Achieving Business intelligence through machine learning is one of the significant issues in recent era. Previously, outliers were being considered as noisy data and disregarded leading to loss of relevant information. This paper highlights the major research challenges in this mining sub domain. It provides a comprehensive taxonomy extracted for Business Intelligence methodologies along with current application sectors. Future research directions and suggestions have been pointed to address this anomaly gap to achieve effective business strategies.
Published in: 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA)
Date of Conference: 29-31 March 2018
Date Added to IEEE Xplore: 30 September 2018
ISBN Information: