About this book series
This series seeks to publish research monographs, collection of papers, and handbooks that focus on analytics and data science. The volumes may focus on applications and advances in a specific domain such as healthcare, sports, hospitality industry, etc. Or these could be based on research in a specific technique or data management issues. The volumes could be a book length project, or a shorter monograph providing review of advances in an emerging area. All compiled volumes will be developed from refereed papers. Such volumes could be selected from a topical conference. Review volumes will undergo a review by the Series Editors of this series.
The following represents a partial (not exclusive) list of topics of interest to this series: Analytics and data science applications – state of the art in virtually any domain such as healthcare, security, retail, hospitality, travel, logistics, organizational management, HR, entertainment, construction, non-profit management, financial services, developing economies, sustainability, etc. Data management issues related to specific industries and how those have been addressed. Each industry has its own legacy data and new data being collected through social media, sensors, transactions, web, etc. These lead to major challenges in how to integrate such data across industries, data munging or wrangling. Practical research and experiences sharing generalizable lessons in these areas will be of particular interest.
The following represents a partial (not exclusive) list of topics of interest to this series: Analytics and data science applications – state of the art in virtually any domain such as healthcare, security, retail, hospitality, travel, logistics, organizational management, HR, entertainment, construction, non-profit management, financial services, developing economies, sustainability, etc. Data management issues related to specific industries and how those have been addressed. Each industry has its own legacy data and new data being collected through social media, sensors, transactions, web, etc. These lead to major challenges in how to integrate such data across industries, data munging or wrangling. Practical research and experiences sharing generalizable lessons in these areas will be of particular interest.
- Electronic ISSN
- 2522-0241
- Print ISSN
- 2522-0233
- Series Editor
-
- Ramesh Sharda,
- Hsinchun Chen
