… Finally, the deep learning algorithm of convolutional neural … performance of data dimension
reduction, feature extraction, … of deep learning algorithms in the artificial intelligence (AI) field, …

… ratio (SNR), difficulty in extracting feature parameters and complexity of classifier model …
based on time-frequency analysis, deep learning and transfer learning fusion model is proposed…

… for handling huge amounts of information. However, the accuracy, … Sentiment analysis in
machine learning refers to automatically determining whether the author of a piece of text is …

… through spatial data analysis… machine learning modeling, using certified recreational sites
for occurrence observations and multisourced social-ecological data as environmental features…

… subtasks: topic extraction, holder identification, claim extraction and sentiment analysis,
followed by an overview of several existing systems. In addition, specific analysis on Chinese …

… to compare social media text data analysis methods and assess their … is a machine
learning-based model, mainly used for topic … review data and reviewer information from April 2006 …

… the full use of spectral information and spatial information in … Deep learning stack machine
model in automatic encoding (… SAE) can effectively extract data in nonlinear information, and …

… are based on statistical rules and deep learning technology respectively. In the … , feature
extraction and classifier selection, are introduced. In the staging method based on deep learning…