Impact of word embedding models on text analytics in deep learning environment: a review
The selection of word embedding and deep learning models for better outcomes is vital.
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
Word embeddings are an n-dimensional distributed representation of a text that attempts to …
Identifying Bulls and bears? A bibliometric review of applying artificial intelligence innovations for stock market prediction
The literature on stock forecasting using the innovative technique of Artificial Intelligence (AI)
has become overwhelming, making it quite challenging for academics and relevant …
has become overwhelming, making it quite challenging for academics and relevant …
Factors affecting text mining based stock prediction: Text feature representations, machine learning models, and news platforms
WC Lin, CF Tsai, H Chen - Applied Soft Computing, 2022 - Elsevier
Text mining techniques have demonstrated their effectiveness for stock market prediction
and different text feature representation approaches,(eg, TF–IDF and word embedding) …
and different text feature representation approaches,(eg, TF–IDF and word embedding) …
Forecasting directional movement of stock prices using deep learning
D Chandola, A Mehta, S Singh, VA Tikkiwal… - Annals of Data …, 2023 - Springer
Stock market's volatile and complex nature makes it difficult to predict the market situation.
Deep Learning is capable of simulating and analyzing complex patterns in unstructured …
Deep Learning is capable of simulating and analyzing complex patterns in unstructured …
Machine learning-based approaches for financial market prediction: A comprehensive review
This research paper investigates the use of machine learning techniques in financial
markets. The paper provides a comprehensive literature review of recent research on …
markets. The paper provides a comprehensive literature review of recent research on …
An analytic review on stock market price prediction using machine learning and deep learning techniques
S Rath, NR Das, BK Pattanayak - Recent Patents on …, 2024 - benthamdirect.com
Anticipating stock market trends is a challenging endeavor that requires a lot of attention
because correctly predicting stock prices can lead to significant rewards if the right …
because correctly predicting stock prices can lead to significant rewards if the right …
How to make machine select stocks like fund managers? Use scoring and screening model
With the development of technology and the abundance of data, many novel methods like
artificial intelligence and machine learning have emerged for quantitative finance. This work …
artificial intelligence and machine learning have emerged for quantitative finance. This work …
Methods for Acquiring and Incorporating Knowledge into Stock Price Prediction: A Survey
Predicting stock prices presents a challenging research problem due to the inherent volatility
and non-linear nature of the stock market. In recent years, knowledge-enhanced stock price …
and non-linear nature of the stock market. In recent years, knowledge-enhanced stock price …
Dual-Attention Based Multi-Path Approach for Intensifying Stock Market Forecasting
In light of the existing challenges in capturing short-term fluctuations and achieving accurate
predictions in stock market time series data, this research presents the “Dual-Attention …
predictions in stock market time series data, this research presents the “Dual-Attention …
Visual recognition and prediction analysis of China's real estate index and stock trend based on CNN-LSTM algorithm optimized by neural networks
N Chen - Plos one, 2023 - journals.plos.org
Today, with the rapid growth of Internet technology, the changing trend of real estate finance
has brought great an impact on the progress of the social economy. In order to explore the …
has brought great an impact on the progress of the social economy. In order to explore the …