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

Chau, M., Huang, Z., & Chen, H. (2003). Teaching key topics in computer science and information systems through a web search engine project. ACM Journal on Educational Resources in Computing, 3(3).

Abstract:

Advances in computer and Internet technologies have made it more and more important for information technology professionals to acquire experience in a variety of aspects, including new technologies, system integration, database administration, and project management. To provide students with a chance to acquire such skills, we designed a project called "Build Your Search Engine in 90 Days," in which students were required to build a domain-specific Web search engine in a semester. In this paper we review the tools and resources available to students and report our experiences in having students to work on this project in a course at the University of Arizona. We also review two tools, called AI Spider and AI Indexer, we developed for students in this project. We highlight a few search engines that were created by the students and suggest some future directions in improving the tools and expanding the project.

Leroy, G., & Chen, H. (2007). Introduction to the special issue on decision support in medicine. Decision Support Systems, 43(4), 1203-1206.

Abstract:

Information technology plays an important role in medicine because of the advanced decision support systems (DSS) it can provide. We provide an overview of the building blocks necessary for a medical decision support system and introduce seven research articles in this special issue that describe the development and evaluation of individual medical DSS building blocks or complete medical DSS. © 2006 Elsevier B.V. All rights reserved.

Zhou, Y., Qin, J., Chen, H., & Nunamaker, J. F. (2005). Multilingual Web retrieval: An experiment on a multilingual business intelligence portal. Proceedings of the Annual Hawaii International Conference on System Sciences, 43-.

Abstract:

The amount of non-English information on the Web has proliferated so rapidly in recent years that it often is difficult for a user to retrieve documents in an unfamiliar language. In this study, we report the design and evaluation of a multilingual Web portal in the business domain in English, Chinese, Japanese, Spanish, and German. Web pages relevant to the domain were collected. Search queries were translated using bilingual dictionaries, while phrasal translation and co-occurrence analysis were used for query translation disambiguation. Pivot translations were also used for language-pairs where bilingual dictionaries were not available. A user evaluation study showed that on average, multilingual performance achieved 72.99% of monolingual performance. In evaluating pivot translation, we found that it achieved 40% performance of monolingual retrieval, which was not as good as direct translation. Overall, our results are encouraging and show promise of successful application of MLIR techniques to Web retrieval.

Chau, M., Wong, C. H., Zhou, Y., Qin, J., & Chen, H. (2010). Evaluating the use of search engine development tools in IT education. Journal of the American Society for Information Science and Technology, 61(2), 288-299.

Abstract:

It is important for education in computer science and information systems to keep up to date with the latest development in technology. With the rapid development of the Internet and the Web, many schools have included Internet-related technologies, such as Web search engines and e-commerce, as part of their curricula. Previous research has shown that it is effective to use search engine development tools to facilitate students' learning. However, the effectiveness of these tools in the classroom has not been evaluated. In this article, we review the design of three search engine development tools, SpidersRUs, Greenstone, and Alkaline, followed by an evaluation study that compared the three tools in the classroom. In the study, 33 students were divided into 13 groups and each group used the three tools to develop three independent search engines in a class project. Our evaluation results showed that SpidersRUs performed better than the two other tools in overall satisfaction and the level of knowledge gained in their learning experience when using the tools for a class project on Internet applications development. © 2009 ASIS & T.

Thuraisingham, B., & Hsinchun, C. (2009). IEEE ISI 2009 welcome message from conference co-chairs. 2009 IEEE International Conference on Intelligence and Security Informatics, ISI 2009.