systematic-review-ai-stock-market-prediction
This repository contains Programming code, citation data, reviews and input variables spreadsheets of systematic review paper: "A systematic review of artificial intelligence prediction techniques for stock market".
https://github.com/chandraveshchaudhari/systematic-review-ai-stock-market-prediction
Science Score: 67.0%
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✓CITATION.cff file
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✓.zenodo.json file
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Found 5 DOI reference(s) in README -
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Links to: zenodo.org -
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○Scientific vocabulary similarity
Low similarity (5.1%) to scientific vocabulary
Repository
This repository contains Programming code, citation data, reviews and input variables spreadsheets of systematic review paper: "A systematic review of artificial intelligence prediction techniques for stock market".
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Metadata Files
README.md
Supplementary Data: A systematic review of artificial intelligence prediction techniques for stock market
Chaudhari, Chandravesh, & Purswani, Geetanjali. (2022). Supplementary Data: A systematic review of artificial intelligence prediction techniques for stock market (1.0.1). Zenodo. https://doi.org/10.5281/zenodo.6750696
Introduction
This repository contains Programming code, citation data, reviews and input variables spreadsheets of systematic review paper:
A Systematic Review Of Artificial Intelligence Prediction Systems For The Stock Market
Authors

Chandravesh chaudhari, Doctoral candidate at CHRIST (Deemed to be University), Bangalore, India under supervision of Dr. Geetanjali purswani.
Owner
- Name: chandravesh chaudhari
- Login: chandraveshchaudhari
- Kind: user
- Repositories: 23
- Profile: https://github.com/chandraveshchaudhari
Citation (CITATION.cff)
cff-version: 1.2.0 message: "If you use this code example, please cite it as below." authors: - family-names: "Chaudhari" given-names: "Chandravesh" orcid: "https://orcid.org/0000-0003-1053-7541" - family-names: "Purswani" given-names: "Geetanjali" orcid: "https://orcid.org/0000-0002-5633-5622" title: "Supplementary Data: A systematic review of artificial intelligence prediction techniques for stock market" doi: 10.5281/zenodo.6750696 date-released: 2022-06-26 url: "https://doi.org/10.5281/zenodo.6750696" publisher: "Zenodo" version: 1.0.1
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