Over the last decade, the explosive growth of Social Media, Instant Message applications together with the improvement of computer performance, networking infrastructures, and storage capabilities have led to the advent of the information age. In fact, in the last decade, the population of industrialized countries with permanent access to the Internet has been severely increased.

This scenario has propitiated the massive dissemination and collection of diverse textual information from multiple (and almost unlimited) data sources. However, the deluge of raw text data is neither meaningful nor useful without the use of proper methodologies to detect and extract valuable knowledge. Knowing relevant information about Internet users in the current digital era is a crucial competitive advantage for industries. As a consequence, several works focused on managing, representing, and exploiting knowledge texts available from textual contents have been developed and introduced during the last years.

This Special Issue aims to publish original research and review articles that explore state-of-the-art methods and tools used to take advantage of textural information. Research using semantic-based and ontology-based approaches for textual problem resolution is welcome. Additionally, tools able to extract knowledge and/or exploit textual information from unstructured and heterogeneous sources are particularly encouraged.

Potential topics include but are not limited to the following:

• Methods for detecting inappropriate content
• Knowledge extraction techniques for textual sources
• Document retrieval systems and methodologies
• Big Data registration, processing and analyses
• Big Data techniques and methodologies, data-driven information systems, and knowledge acquisition
• Semantic and knowledge-based systems
• Multi-classifier/Decision Systems
• Natural Processing techniques for improving textual management
• Using ontologies knowledge to enhance textual problems resolution and ontology learning from text