Hsinchun Chen

Hsinchun Chen

Professor, Management Information Systems
Regents Professor
Member of the Graduate Faculty
Professor, BIO5 Institute
Primary Department
Contact
(520) 621-4153

Research Interest

Dr Chen's areas of expertise include:Security informatics, security big data; smart and connected health, health analytics; data, text, web mining.Digital library, intelligent information retrieval, automatic categorization and classification, machine learning for IR, large-scale information analysis and visualization.Internet resource discovery, digital libraries, IR for large-scale scientific and business databases, customized IR, multilingual IR.Knowledge-based systems design, knowledge discovery in databases, hypertext systems, machine learning, neural networks computing, genetic algorithms, simulated annealing.Cognitive modeling, human-computer interactions, IR behaviors, human problem-solving process.

Publications

Roche, E. M., Goodman, S. E., & Chen, H. (1992). The Landscape of International Computing. Advances in Computers, 35(C), 325-371.
Chen, H. (2005). Introduction to the special topic issue: Intelligence and security informatics. Journal of the American Society for Information Science and Technology, 56(3), 217-220.
Qin, J., Zhou, Y., Reid, E., Lai, G., & Chen, H. (2007). Analyzing terror campaigns on the internet: Technical sophistication, content richness, and Web interactivity. International Journal of Human Computer Studies, 65(1), 71-84.

Abstract:

Terrorists and extremists are increasingly utilizing Internet technology to enhance their ability to influence the outside world. Due to the lack of multi-lingual and multimedia terrorist/extremist collections and advanced analytical methodologies, our empirical understanding of their Internet usage is still very limited. To address this research gap, we explore an integrated approach for identifying and collecting terrorist/extremist Web contents. We also propose a Dark Web Attribute System (DWAS) to enable quantitative Dark Web content analysis from three perspectives: technical sophistication, content richness, and Web interactivity. Using the proposed methodology, we identified and examined the Internet usage of major Middle Eastern terrorist/extremist groups. More than 200,000 multimedia Web documents were collected from 86 Middle Eastern multi-lingual terrorist/extremist Web sites. In our comparison of terrorist/extremist Web sites to US government Web sites, we found that terrorists/extremist groups exhibited similar levels of Web knowledge as US government agencies. Moreover, terrorists/extremists had a strong emphasis on multimedia usage and their Web sites employed significantly more sophisticated multimedia technologies than government Web sites. We also found that the terrorists/extremist groups are as effective as the US government agencies in terms of supporting communications and interaction using Web technologies. Advanced Internet-based communication tools such as online forums and chat rooms are used much more frequently in terrorist/extremist Web sites than government Web sites. Based on our case study results, we believe that the DWAS is an effective tool to analyse the technical sophistication of terrorist/extremist groups' Internet usage and could contribute to an evidence-based understanding of the applications of Web technologies in the global terrorism phenomena. © 2006 Elsevier Ltd. All rights reserved.

Jennifer, X. u., & Chen, H. (2003). Untangling criminal networks: A Case study. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2665, 232-248.

Abstract:

Knowledge about criminal networks has important implications for crime investigation and the anti-terrorism campaign. However, lack of advanced, automated techniques has limited law enforcement and intelligence agencies' ability to combat crime by discovering structural patterns in criminal networks. In this research we used the concept space approach, clustering technology, social network analysis measures and approaches, and multidimensional scaling methods for automatic extraction, analysis, and visualization of criminal networks and their structural patterns. We conducted a case study with crime investigators from the Tucson Police Department. They validated the structural patterns discovered from gang and narcotics criminal enterprises. The results showed that the approaches we proposed could detect subgroups, central members, and between-group interaction patterns correctly most of the time. Moreover, our system could extract the overall structure for a network that might be useful in the development of effective disruptive strategies for criminal networks. © Springer-Verlag Berlin Heidelberg 2003.

Chung, W., & Chen, H. (2009). Browsing the underdeveloped web: An experiment on the arabic medical web directory. Journal of the American Society for Information Science and Technology, 60(3), 595-607.

Abstract:

While the Web has grown significantly in recent years, some portions of the Web remain largely underdeveloped, as shown in a lack of high-quality content and functionality. An example is the Arabic Web, in which a lack of well-structured Web directories limits users' ability to browse for Arabic resources. In this research, we proposed an approach to building Web directories for the underdeveloped Web and developed a proof-of-concept prototype called the Arabic Medical Web Directory (AMed- Dir) that supports browsing of over 5,000 Arabic medical Web sites and pages organized in a hierarchical structure. We conducted an experiment involving Arab participants and found that the AMedDir significantly outperformed two benchmark Arabic Web directories in terms of browsing effectiveness, efficiency, information quality, and user satisfaction. Participants expressed strong preference for the AMedDir and provided many positive comments. This research thus contributes to developing a useful Web directory for organizing the information in the Arabic medical domain and to a better understanding of how to support browsing on the underdeveloped Web.