Machine Learning and Data Mining for User Classification

Dear Colleagues,

The modern Internet is characterized by its many users, the multitude of web services offered, and the increased complexity of accessing digital resources. In this context, an increased number and more sophisticated threats have occurred, requiring new methods for protecting and facilitating users. Also, the large amount of stored raw data, which is growing at a dizzying pace daily, hides information that is not immediately available and requires time and effort.

This Special Issue suggests new approaches for creating user profiles to protect unsuspecting users, enhancing user authentication, and extracting information from textual data. Moreover, this Special Issue is interested in document classification and, generally, for methods protecting Internet users, making better use of the services offered, and extracting the available information using data derived mainly from text and typing.

Dr. Ioannis Tsimperidis
Dr. Eleni Vrochidou
Prof. Dr. George A. Papakostas
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 1600 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.

• data mining
• information retrieval
• text analysis
• data clustering
• user authentication
• user profiling
• user classification by inherent and acquired characteristics
• natural language processing
• author classification
• keystroke dynamics
• typing pattern recognition
• content classification
• digital text forensics
• typing behavior