Data Science for Social Good — 2014 KDD Highlights

Authors

  • Wei Wang University of California, Los Angeles

DOI:

https://doi.org/10.1609/aaai.v29i1.9351

Keywords:

Data mining

Abstract

As the premier international forum for data science, data mining, knowledge discovery and big data, the ACM SIGKDD Conference on Knowledge Discovery and Data Mining (KDD) brings together researchers and practitioners from academia, industry, and government to share their ideas, research results and experiences. Partnered with Bloomberg, it celebrated its 20th years in 2014 with the theme “Data Science for Social Good”. The breadth of topics covered in the 2014 research program is truly comprehensive and nicely balanced among social and information networks, data mining for social good, graph mining, statistical techniques for big data, topic modeling, recommender systems, data streams, scalable methods, Web mining, clustering, feature selection, applications to health care and medicine, public safety, advertising, social analytics, personalization, workforce analytics, health, and many more.

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Published

2015-03-04

How to Cite

Wang, W. (2015). Data Science for Social Good — 2014 KDD Highlights. Proceedings of the AAAI Conference on Artificial Intelligence, 29(1). https://doi.org/10.1609/aaai.v29i1.9351