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

Chen, H. (1999). Semantic research for digital libraries. D-Lib Magazine, 5(10), 52-65.
Chau, M., Qin, J., Zhou, Y., Tseng, C., & Chen, H. (2008). SpidersRUs: Creating specialized search engines in multiple languages. Decision Support Systems, 45(3), 621-640.

Abstract:

While small-scale search engines in specific domains and languages are increasingly used by Web users, most existing search engine development tools do not support the development of search engines in languages other than English, cannot be integrated with other applications, or rely on proprietary software. A tool that supports search engine creation in multiple languages is thus highly desired. To study the research issues involved, we review related literature and suggest the criteria for an ideal search tool. We present the design of a toolkit, called SpidersRUs, developed for multilingual search engine creation. The design and implementation of the tool, consisting of a Spider module, an Indexer module, an Index Structure, a Search module, and a Graphical User Interface module, are discussed in detail. A sample user session and a case study on using the tool to develop a medical search engine in Chinese are also presented. The technical issues involved and the lessons learned in the project are then discussed. This study demonstrates that the proposed architecture is feasible in developing search engines easily in different languages such as Chinese, Spanish, Japanese, and Arabic. © 2007 Elsevier B.V. All rights reserved.

Jiang, S., Gao, Q., & Chen, H. (2013). Statistical modeling of nanotechnology knowledge diffusion networks. International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design, 4, 3552-3571.

Abstract:

Nanotechnology is crucial for industrial and scientific advancement, with millions of dollars being invested each year in nanotechnology-related research. Recent developments in information-technology enables modeling the knowledge diffusion process via online depositories of nanotechnology-related scientific publication records. Understanding the mechanism may help funding agencies use their funding effectively. This study uses Exponential Random Graph Models (ERGMs), a family of theorygrounded statistical models, to explore the knowledge diffusion patterns among nanotechnology researchers. We systematically evaluate how various attributes of researchers and public funding affect the knowledge diffusion processes. Results show that the impact of public funding on nanotechnology knowledge transfer has been increasing in recent years. Funding all kinds of researchers can stimulate knowledge transfer. Also, funding senior researchers help stimulate knowledge sharing. Our analysis framework of knowledge diffusion networks is effective in studying the knowledge diffusion patterns in nanotechnology, and can be easily applied to other fields. © (2013) by the AIS/ICIS Administrative Office All rights reserved.

Dang, Y., Zhang, Y., Hu, P. J., Brown, S. A., & Chen, H. (2011). Knowledge mapping for rapidly evolving domains: A design science approach. Decision Support Systems, 50(2), 415-427.

Abstract:

Knowledge mapping can provide comprehensive depictions of rapidly evolving scientific domains. Taking the design science approach, we developed a Web-based knowledge mapping system (i.e., Nano Mapper) that provides interactive search and analysis on various scientific document sources in nanotechnology. We conducted multiple studies to evaluate Nano Mapper's search and analysis functionality respectively. The search functionality appears more effective than that of the benchmark systems. Subjects exhibit favorable satisfaction with the analysis functionality. Our study addresses several gaps in knowledge mapping for nanotechnology and illustrates desirability of using the design science approach to design, implement, and evaluate an advanced information system. © 2010 Elsevier B.V. All rights reserved.

Zhu, B., & Chen, H. (2005). Information visualization. Annual Review of Information Science and Technology, 39, 139-177.