Categories |
DATA SCIENCE
MACHINE LEARNING
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About |
We are living in the age of data, where nearly every task we conduct in our daily lives depends on data and can be tracked and supported digitally. Massive data of different types, including numeric variables, images, videos, music, text, etc., could be collected when shopping, working, socializing, communicating, relaxing and traveling, as part of our daily lives. As a multi-disciplinary field that integrates mathematics, statistics and computer science, data science uses scientific methods, processes, algorithms and systems to extract knowledge and insights from structured and unstructured data, with the ultimate goal to support decision making. In this context, recommender systems have been one of the most important applications of data science. Recommender systems use advanced analytics and learning techniques to select relevant and significant information from massive data and inform users’ smart decision-making on their daily needs. |
Call for Papers |
The special issue invites submissions on all topics of data science for recommender systems, including but not limited to: |
Credits and Sources |
[1] Recommender systems 2020 : Data Science for Next-Generation Recommender Systems with International Journal of Data Science and Analytics |