Cited by 10Recommender Systems and TechniquesAdvanced Bandit Algorithms ResearchArtificial Intelligence Applications

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

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Perichappan, Kumar Attangudi Perichiappan·2018·Journal of Computer and Communications

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.

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Metadata

Authors
Perichappan, K. A. P.
Affiliations
KPMG (United States) (US)
Corresponding author
Perichappan, Kumar Attangudi Perichiappan
Venue
Journal of Computer and Communications
Published
2018
Volume
06
Issue
06
Pages
45-53
ISSN
  • 2327-5219 (ISSN-L)
  • 2327-5227
OpenAlex
W2810997783
Cited by
10
References
0
Citations by year
2024: 1 · 2021: 6 · 2020: 2 · 2019: 1
FWCI
3.63
Type
journal article
Language
en
Open access
Locations
Journal of Computer and Communications (publishedVersion, cc-by)
Topics
  • Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Advanced Bandit Algorithms Research
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Intelligence Applications
Keywords
greedy algorithm, deep learning, user behavior prediction, decision support, artificial intelligence

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CoChat. (2026). Citation check: Greedy Algorithm Based Deep Learning Strategy for User Behavior Prediction and Decision Making Support. https://app.cochat.ai/papers/10.4236/jcc.2018.66004
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Perichappan, K. A. P. (2018). Greedy Algorithm Based Deep Learning Strategy for User Behavior Prediction and Decision Making Support. Journal of Computer and Communications. https://doi.org/10.4236/jcc.2018.66004