AI Text: Text Mining, Tools, Algorithms, Applications, and Challenges
A special issue of Mathematical and Computational Applications (ISSN 2297-8747).
Deadline for manuscript submissions: 15 August 2025 | Viewed by 804
Special Issue Editors
Interests: convolutional neural network; graph convolutional network; neural network; training set; random walk; support vector machine; baseline methods; feature maps; heterogeneous network; recurrent neural network; self-supervised learning; attention layer
Special Issue Information
Dear Colleagues,
Text mining has developed as the main domain in machine learning and data mining. Text mining plays an important role in numerous application domains, from information extraction, text classification, information retrieval, and neural networks to sentiment analysis and text summarization. Several mining methods have been proposed recently, including clustering, support vector machines, deep learning, neural networks, and rule-based and statistics-based models. Distance and similarity estimation has always been key in each category.
The purpose of this Special Issue is to offer the opportunity to publish innovative research articles: novel applications, cutting-edge theories, and innovative algorithms. Specifically, we welcome manuscripts from text summarization and mining, commonly regarded as the most challenging area of text mining.
Topics include, but are not limited to, the following:
- Sentiment analysis;
- Information retrieval and extraction;
- Question-answering systems;
- Security and privacy;
- Text classification;
- Text summarization;
- Recommendation systems.
Prof. Dr. Xuequn Shang
Guest Editor
Dr. Samer Waheeb
Guest Editor Assistant
Manuscript Submission Information
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Keywords
- machine learning and data mining
- neural networks
- information retrieval
- text summarization
- information extraction
- recommendation systems
- text mining
- sentiment analysis
- deep learning
- information hiding
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