Text Mining, Machine Learning, and Natural Language Processing

Dear Colleagues,

This Special Issue will address text mining techniques to perform different tasks on textual data. Text mining uses techniques from machine learning and natural language processing to perform a set of tasks, such as knowledge extraction, information extraction, summarization, name entity extraction, relations extraction, text embeddings, sentiment classification, topic modelling, fake news identification, and others.

Topics of interest include but are not limited to the following:

• Text classification and clustering;
• Text representation using word, sentence, and document embeddings;
• Text preprocessing using NLP techniques;
• Text summarization;
• Web and social content mining;
• Information and knowledge extraction from textual corpora;
• Text mining applications in different domains, such as legal, news, and biomedical;
• Sentiment classification;
• Opinion mining;
• Topic modeling.

Prof. Dr. Ahmed Rafea
Prof. Dr. Julian Szymanski
Guest Editors

Manuscript Submission Information

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Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.