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

Hsu, F., Hu, P. J., & Chen, H. (2006). Examining the business-technology alignment in government agencies: A study of electronic record management systems in Taiwan. PACIS 2006 - 10th Pacific Asia Conference on Information Systems: ICT and Innovation Economy, 1090-1106.

Abstract:

For e-government to succeed, government agencies must manage their records and archives of which the sheer volume and diversity necessitate the use of electronic record management systems (ERMS). Using an established business-technology alignment model, we analyze an agency's strategic alignment choice and examine the outcomes and agency performance associated with that alignment. The specific research questions addressed in the study are as follows: (1) Do strategic alignment choices vary among agencies that differ in purpose or position within the overall government hierarchy? (2) Do agencies' alignment choices lead to different outcomes? and (3) Does performance in implementing, operating, and using ERMS vary among agencies that follow different alignment choices? We conducted a large-scale survey study of 3,319 government agencies in Taiwan. Our data support the propositions tested. Based on the findings, we discuss their implications for digital government research and practice.

Zhu, B., & Chen, H. (2005). Using 3D interfaces to facilitate the spatial knowledge retrieval: A geo-referenced knowledge repository system. Decision Support Systems, 40(2), 167-182.

Abstract:

Retrieving knowledge from a knowledge repository includes both the process of finding information of interest and the process of converting incoming information to a person's own knowledge. This paper explores the application of 3D interfaces in supporting the retrieval of spatial knowledge by presenting the development and the evaluation of a geo-referenced knowledge repository system. As computer screen is crowded with high volume of information available, 3D interface becomes a promising candidate to better use the screen space. A 3D interface is also more similar to the 3D terrain surface it represents than its 2D counterpart. However, almost all previous empirical studies did not find any supportive evidence for the application of 3D interface. Realizing that those studies required users to observe the 3D object from a given perspective by providing one static interface, we developed 3D interfaces with interactive animation, which allows users to control how a visual object should be displayed. The empirical study demonstrated that this is a promising approach to facilitate the spatial knowledge retrieval. © 2004 Elsevier B.V. All rights reserved.

Chen, H., & Yang, C. C. (2011). Special issue on social media analytics: Understanding the pulse of the society. IEEE Transactions on Systems, Man, and Cybernetics Part A:Systems and Humans, 41(5), 826-.
Lin, Y., Chen, H., Brown, R., Li, S., & Yang, H. (2017). Healthcare Predictive Analytics for Risk Profiling in Chronic Care: A Bayesian Multi-Task Learning Approach. MIS Quarterly, 41(2), 473-495.
Chen, H., Nunamaker Jr., J., Orwig, R., & Titkova, O. (1998). Information visualization for collaborative computing. Computer, 31(8), 75-81.

Abstract:

A prototype tool classifies output from an electronic meeting system into a manageable list of concepts, topics, or issues that a group can further evaluate. In an experiment with output from the GroupSystems electronic meeting system, the tool's recall ability was comparable to that of a human facilitator, but took roughly a sixth of the time.