The recent advancements in intelligent sensing, embedded internet, edge computing, and predictive data mining permeate intelligence and decision making into the physical world which continuously enhances the human experience in real-time. The Web has become a ubiquitous tool for finding/sharing information and conducting business, learning, and entertainment. Web Intelligence (WI) strives to develop innovative solutions and frameworks that deepen the understanding of the computational, logical, cognitive, physical, and social foundations of the future Web. The Sentiment Web, the Sentient-Sensory Web, the Synergistic Web, and the Solution-Savvy Web collectively lead to the intelligence of the “Web”. Typical applications of WI such as online text classification, Web document clustering, Web recommender for e-commerce, Web usage profiling, and similar knowledge discovery tasks are drawing attention from communities of global researchers. Simultaneously, nature-inspired computing (NIC) has emerged as a paradigm of problem-solving that mimics a natural system or process to construct a robust and optimal solution. It represents an important research field in computational intelligence, soft computing, and optimization for solving a large number of real-world problems in almost all areas of engineering. Researchers and scientists study how biological groups, like ant colonies, beehives, and flocks of birds, react to stimuli, process information, and make decisions. The analogies and abstractions developed in these fields have been able to provide valuable insights to solve complex real-world problems, in many cases producing human-competitive results.

The knowledge-intensive and intelligent service Web generates a substantial amount of data that often contains complex attributes. Moreover, it is unstructured and is generated asynchronously, dynamically from Web activities. For example, the Web usage data. To deal with big data which is essential to Web Intelligence and related applications, it calls for advanced analytics and machine learning algorithms for supporting knowledge discovery. Lately, NIC has been applied to solving real-world problems in data analytics and pattern recognition. Undoubtedly, WI presents excellent opportunities and challenges for the research and development of new generation Web-based information processing technology as well as for exploiting business intelligence; NIC can optimize this dynamically changing and unpredictable task environment.

This Special Issue encourages original research and review articles describing innovative solutions and new research advances in the general areas related to the theoretical foundations of nature-inspired computing and its applications in various web intelligence domains. Research papers based on theoretical or experimental contributions expounding this synergy of nature-inspired computing and web intelligence are welcome.

Potential topics include but are not limited to the following:

• Cognitive models of Web Intelligence
• Data mining for Web Intelligence
• Web mining using nature-inspired computing
• Learning user profiles using nature-inspired computing
• Web surfing and internet congestion using nature-inspired computing
• Nature-inspired recommender models on the Web
• Nature-inspired clustering algorithms for Web Intelligence data
• Web document classification using nature-inspired computing
• Semantic Web and nature-inspired computing
• Collective intelligence and the Web (agents, self-organizing systems, crowdsourcing)
• Data science and the Web (big data applications, blog/twitter analysis, sentiment and opinion mining, multimedia, mobile, spatial, temporal, and graph data mining)
• Social network analysis and Web blog mining using nature-inspired computing
• Network science (social network analysis, intelligent ubiquitous Web, IoT, wearable technology)
• Web security, integrity, privacy, and trust using nature-inspired computing