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Curme, C., Preis, T., Stanley, H.E. and Moat, H.S. (2014) Quantifying the Semantics of Search Behavior before Stock Market Moves. Proceedings of the National Academy of Sciences, 111, 11600-11605.
https://doi.org/10.1073/pnas.1324054111

has been cited by the following article:

• TITLE: Greedy Algorithm Based Deep Learning Strategy for User Behavior Prediction and Decision Making Support

  AUTHORS: Kumar Attangudi Perichiappan Perichappan

  KEYWORDS: Machine Learning, Big Data Analysis, Decision Making, Artificial Intelligence, Computer Science, Tensorflow, Prediction

  JOURNAL NAME: Journal of Computer and Communications, Vol.6 No.6, June 27, 2018

  ABSTRACT: In this paper, we suggest a deep learning strategy for decision support, based on a greedy algorithm. Decision making support by artificial intelligence is of the most challenging trends in modern computer science. Currently various strategies exist and are increasingly improved in order to meet practical needs of user-oriented platforms like Microsoft, Google, Amazon, etc.