Human behavior analysis for library and information science (Editorial)
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This special issue investigates the topics of human behavior analysis, data mining, and ambient intelligence technologies in library and information sciences. It is considered one of the most important issues to investigate the interaction between librarians and technology. Recently, the emerging technologies like Internet of Things, big data, and deep learning technologies, along with the public?s embracing of wireless sensor networks generates new opportunities for situation-aware library systems and services. The realization of big data covers the main kernel of database management technology, giving rise to the development of raw data gathering, data preprocessing, data warehouse, specific hardware devices, computer clouds, parallel processing techniques, and data mining. Compared to traditional library
systems and services, a situation-aware, computing-based library application has the
advantage of changing from the on-spot experiences to the mobile and ubiquitous environment.
Many challenges, however, must be addressed for the development of consistent, suitable, safe and flexible real-time library and information systems. Deficiencies in human
behavior analysis and situation-aware care may raise issues in the collection of streamed data. The analysis and use of such data refers to as social mining, web mining and sentiment mining, the last of which has recently become highly popular. Situation-aware technology involves the creation of smart spaces and this technology can be applied to systems that handle information retrieval, recommendations, trust, agent behavior, environmental conditions and changes and security, etc., and the surrounding issues have important implications to library and information science.