V. Dhar, "Data Science and Prediction," Commun. ACM, vol. 56, no. 12, pp. 64-73, 2012.Dhar, Vasant. "Data science and prediction." Communications of the ACM 56.12 (2013): 64-73. Digital Ecosystems and Business Intelligence Institute Quality and Interestingness of Association Rules ...
Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64–73. https://doi.org/10.1145/2500499 Readers over time ‘12‘14‘16‘18‘20‘22‘24055110165220 Readers' Seniority PhD / Post grad / Masters / Doc 438 73% Researcher 70 12% Professor / Associate Prof...
A data science research methodology is becoming even more important in an educational context. More specifically, this field urgently requires more studies, especially related to outcome measurement and prediction and linking these to specific interventions. Consequently, the purpose of this paper is ...
According to Vasant Dhar of the Stern School of Business (Data Science and Prediction), Jeff Leek (The key word in “Data Science” is not Data, it is Science), and repeated on Wikipedia, “In general terms, data science is the extraction of knowledge from data”. Well, excuse me if ...
What is data science? Vasant Dhar, a professor at the Stern School of Business, offered the following definition:“Data science is the study of the generalizable extraction of knowledge from data”.Though it is one of the most commonly used definitions of data science, it requires a more ...
Dhar, V. Data Science and Prediction. Commun. ACM 2013, 56, 64–73. [Google Scholar] [CrossRef] Wladowsky-Berger, I. Why Do We Need Data Science When We’ve Had Statistics for Centuries? Wall Street J. Available online: https://blogs.wsj.com/cio/2014/05/02/why-do-we-need-data-...
Dhar, V. Data science and prediction. Commun. ACM 2013, 56, 64–73. [CrossRef] 6. Drineas, P.; Huo, X. NSF Workshop Report: Theoretical Foundations of Data Science (TFoDS); TFoDS workshop organizing committee: Arlington, VA, USA, 2016; 20p. Available online: http://www.cs.rpi....
Keywords 1. Introduction 2. A normative perspective of Big Data: challenges and analytical methods 3. Research methodology 4. Big Data and Big Data Analytics: findings and analysis 5. Conclusions Appendix A. ReferencesShow full outline Figures (11) Show 5 more figures Tables (1) TableJournal...
It just remains in a repetitive ‘me too’ point-and-click science ‘group-think’. Such a low-performing institutional culture - without deeper reflection on progress—a missing vision—still dominates, e.g., in regular SDMs the use of just a few predictors and Maximum Entropy (Maxent) (...