Data science and prediction

By Vasant Dhar. CACM, 2013

828 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/1163c2996dfd0a46639b094e34ad783e969a0692

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In Artificial Intelligence

Citations in the corpus

Editorial - Big Data, Data Science, and Analytics: The Opportunity and Challenge for IS Research (2014, background): “Prediction as an initial basis for theory building also has particular value in a world where patterns often emerge before the reasons for them become apparent (Dhar 2013).”
Towards Data Science (2015, background): “Dhar (2013) mentions that the implications of data science include the question of how scientists could use big data to their benefit in scientific inquiries.”
Big Data and Data Science Methods for Management Research (2016, background): “Data science emphasizes the systematic study of the organization, properties, and analysis of data and their role in inference, including our confidence in the inference (Dhar, 2013).”
CRISP-DM Twenty Years Later: From Data Mining Processes to Data Science Trajectories (2021, background): “[65], [66], [67], [68], and they are usually associated with the exploration activities.”
Evolutionary Fuzzy Systems for Explainable Artificial Intelligence: Why, When, What for, and Where to? (2019, background): “Therefore, a movement is being witnessed from traditional data mining towards a more profitable and challenging scenario known as data science [3].”
Human-AI Collaboration in Data Science (2019, background): “Data science is amulti-disciplinary field focused on generalizable processes for extracting knowledge and insights from data [8].”
ChartDialogs: Plotting from Natural Language Instructions (2020, methodology): “This obstacle, coupled with the increasing popularity of the scientiﬁc method of gleaning information from data (Hey et al., 2009; Dhar, 2013), motivates our objective of designing natural language interfaces (NLIs) for plotting.”