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Human Behavior Analysis for Library and Information Science

Special issue call for papers from Library Hi Tech

Write for a journal with an Impact Factor of 0.798

This special issue will investigate human behavior analysis and situation-aware technology in library and information sciences. The interaction between librarians and technology has been a popular research topic. The rapid growth of the Internet of Things and big data technology, 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 core issues of database technology, giving rise to the development of raw data collection, data preprocessing, storage structures, and data mining for the efficient management of very large data volumes. Compared to traditional library systems and services, a situation-aware, computing-based library application has the advantage of changing from the on-spot mode to in-mobility and in-ubiquitous modes.

However, many challenges must be addressed if we are to develop consistent, suitable, safe and flexible real-time library and information systems. Deficiencies in human behavior analysis and situation-aware care can cause issues in the collection of streamed data. The analysis and use of such data is referred 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 location-based service applications that integrate information from independent systems which autonomously and securely support human activities. This technology can be applied to systems that handle information retrieval, recommendations, trust and security, etc., and the surrounding issues have important implications to library and information science.

This special issue of the journal will explore the use of information technology to perform human behavior analysis in library and information science. We encourage the submission of original works based on interdisciplinary research (e.g., computer science and humanistic disciplines such as sociology and anthropology). This issue will cover both technological and non-technological issues related to these rapidly growing and evolving areas.

Thus, we invite authors to submit papers related (but not exclusive) to the following topics:

Application Areas

  • e-Learning, m-Learning, u-Learning
  • Information Centers
  • Libraries and Digital Libraries
  • Museums
  • Virtual Learning Environments


  • Ambient Intelligence
  • Context-Aware Computing
  • Data Mining and Big Data Mining
  • Evolving Soft Computing Techniques
  • Human-to-Computer Interfaces
  • Human-Machine Interaction
  • Machine Learning and Vision
  • Modeling Environments and Human Behavior
  • Security, Privacy and Trust
  • Sentiment Mining
  • Situation-Aware Systems
  • Social Mining Computing
  • Text Mining

Important dates

Submission due: 31st January, 2017
Notification of final acceptance: 31 March, 2017
Final papers: 30 April, 2017


Submissions to the special issue will be screened by the Special Issue Editors to insure that they conform to the quality standards of Library Hi Tech Journal. Papers that do not pass this initial screening will be immediately returned to the authors. Reviewers will apply those standards in forming recommendations for acceptance, revision, or rejection. A maximum of two revisions will be invited. Papers should be formatted with Library Hi Tech Journal style, please see the author guidlines here. The submission deadline is January 31st 2017.

The prospective contributors should submit their papers directly to the online submission system. In addition, Authors please note the Special Issue (Human Behavior Analysis for Library and Information Science) and Guest Editor Name (Dr. Mu-Yen Chen, Dr. Edwin Lughofer, Dr. Neil Yen, and Dr. Chia-Chen Chen) in the cover letter with submission.

Guest Editors

Mu-Yen Chen, Ph.D
Department of Information Management
National Taichung University of Science and Technology, Taiwan
E-mail: [email protected]

Edwin David Lughofer, Ph.D
Department of Knowledge-Based Mathematical Systems
Johannes Kepler University Linz, Linz, Austria
E-mail: [email protected] 

Neil Y. Yen, Ph.D
System Intelligence Laboratory,
The University of Aizu, Japan
E-Mail: [email protected]

Chia-Chen Chen, Ph.D
Department of Management Information Systems
National Chung Hsing University, Taiwan
E-Mail: [email protected]