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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

A Numerical-Based Attention Method for Stock Market Prediction With Dual Information
Guang Liu, Xiaojie Wang
IEEE Access (2018) Vol. 7, pp. 7357-7367
Open Access | Times Cited: 56

Showing 1-25 of 56 citing articles:

Applications of deep learning in stock market prediction: Recent progress
Weiwei Jiang
Expert Systems with Applications (2021) Vol. 184, pp. 115537-115537
Open Access | Times Cited: 472
Deep Learning for Stock Market Prediction
Mojtaba Nabipour, Pooyan Nayyeri, Hamed Jabani, et al.
Entropy (2020) Vol. 22, Iss. 8, pp. 840-840
Open Access | Times Cited: 282
An efficient stock market prediction model using hybrid feature reduction method based on variational autoencoders and recursive feature elimination
Hakan Gündüz
Financial Innovation (2021) Vol. 7, Iss. 1
Open Access | Times Cited: 57
A hybrid two-stage financial stock forecasting algorithm based on clustering and ensemble learning
Ying Xu, Cuijuan Yang, Shaoliang Peng, et al.
Applied Intelligence (2020) Vol. 50, Iss. 11, pp. 3852-3867
Closed Access | Times Cited: 59
Stocks of year 2020: prediction of high variations in stock prices using LSTM
Gourav Bathla, Rinkle Rani, Himanshu Aggarwal
Multimedia Tools and Applications (2022) Vol. 82, Iss. 7, pp. 9727-9743
Closed Access | Times Cited: 32
Diffusion Variational Autoencoder for Tackling Stochasticity in Multi-Step Regression Stock Price Prediction
Kelvin J. L. Koa, Yunshan Ma, Ritchie Ng, et al.
(2023), pp. 1087-1096
Open Access | Times Cited: 14
Machine Learning Based Stock Market Analysis: A Short Survey
Hrishikesh Vachhani, Mohammad S. Obiadat, Arkesh Thakkar, et al.
Lecture notes on data engineering and communications technologies (2020), pp. 12-26
Closed Access | Times Cited: 35
Big data based stock trend prediction using deep CNN with reinforcement-LSTM model
Ishwarappa, J. Anuradha
International Journal of Systems Assurance Engineering and Management (2021)
Closed Access | Times Cited: 27
Forecasting Fluctuations in the Financial Index Using a Recurrent Neural Network Based on Price Features
Lin Yufei, Tzu-Ming Huang, Wei‐Ho Chung, et al.
IEEE Transactions on Emerging Topics in Computational Intelligence (2020) Vol. 5, Iss. 5, pp. 780-791
Closed Access | Times Cited: 28
Graph-Based Stock Recommendation by Time-Aware Relational Attention Network
Jianliang Gao, Xiaoting Ying, Cong Xu, et al.
ACM Transactions on Knowledge Discovery from Data (2021) Vol. 16, Iss. 1, pp. 1-21
Closed Access | Times Cited: 26
Enhancing stock price prediction using GANs and transformer-based attention mechanisms
S. Li, Sijie Xu
Empirical Economics (2024)
Open Access | Times Cited: 3
Stock Market Prediction with Historical Time Series Data and Sentimental Analysis of Social Media Data
Kesavan Muralidharan, J. Karthiraman, Rajadurai T. Ebenezer, et al.
2022 6th International Conference on Intelligent Computing and Control Systems (ICICCS) (2020), pp. 477-482
Closed Access | Times Cited: 25
Recent Advances in Stock Market Prediction Using Text Mining: A Survey
Faten Alzazah, Xiaochun Cheng
IntechOpen eBooks (2020)
Open Access | Times Cited: 23
On the Economic Significance of Stock Market Prediction and the No Free Lunch Theorem
Carlos Bousoño‐Calzón, Josue Bustarviejo-Munoz, Pedro Aceituno Aceituno, et al.
IEEE Access (2019) Vol. 7, pp. 75177-75188
Open Access | Times Cited: 22
Using Fuzzy Inference Systems for the Creation of Forex Market Predictive Models
Amaury Hernández-Águila, Mario García-Valdéz, J. J. Merelo, et al.
IEEE Access (2021) Vol. 9, pp. 69391-69404
Open Access | Times Cited: 19
A Review of Sentiment, Semantic and Event-Extraction-Based Approaches in Stock Forecasting
Wai Khuen Cheng, Khean Thye Bea, Steven Mun Hong Leow, et al.
Mathematics (2022) Vol. 10, Iss. 14, pp. 2437-2437
Open Access | Times Cited: 13
Developing a Novel Hybrid Model Double Exponential Smoothing and Dual Attention Encoder-Decoder Based Bi-Directional Gated Recurrent Unit Enhanced With Bayesian Optimization to Forecast Stock Price
Talabathula Jayanth, A. Manimaran
IEEE Access (2024) Vol. 12, pp. 114760-114785
Open Access | Times Cited: 2
Multi-Scale RCNN Model for Financial Time-series Classification
Guang Liu, Xiaojie Wang, Ruifan Li
arXiv (Cornell University) (2019)
Open Access | Times Cited: 13
Do bitcoin news information flow and return volatility fit the sequential information arrival hypothesis and the mixture of distribution hypothesis?
Ke-Hsin Chou, Min-Yuh Day, Chien-Liang Chiù
International Review of Economics & Finance (2023) Vol. 88, pp. 365-385
Closed Access | Times Cited: 4
Development of a stock trading system based on a neural network using highly volatile stock price patterns
Jangmin Oh
PeerJ Computer Science (2022) Vol. 8, pp. e915-e915
Open Access | Times Cited: 4
Explainable Deep Learning for Thai Stock Market Prediction Using Textual Representation and Technical Indicators
Tanawat Chiewhawan, Peerapon Vateekul
(2020), pp. 19-23
Closed Access | Times Cited: 5
Comparative Study of Stock Price Prediction using Machine Learning
Parag P. Kadu, G. R. Bamnote
2022 7th International Conference on Communication and Electronics Systems (ICCES) (2021) Vol. 101, pp. 1200-1204
Closed Access | Times Cited: 5
Quantitative Analysis and Sentiment Analysis for Stock Price Forecast: The Case of Colombo Stock Exchange
M. B. D. Pavithya, G. S. D. Perera, Saubhagya Munasinghe, et al.
(2021), pp. 512-517
Closed Access | Times Cited: 5
Prediction of Intraday Trend Reversal in Stock Market Index Through Machine Learning Algorithms
K. S. Uma, Srinath R. Naidu
Advances in intelligent systems and computing (2020), pp. 331-341
Closed Access | Times Cited: 4
Commodities Exchange Utilizing Diverse Deep Learning Algorithm
Anitha Julian, R. Akash, Chennakampalli Reddy, et al.
(2024)
Open Access
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