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

Hauck, R. V., Atabakhsh, H., Ongvasith, P., Gupta, H., & Chen, H. (2002). Using coplink to analyze criminal-justice data. Computer, 35(3), 30-37.

Abstract:

The Coplink project has been initiated to address the problems in criminal justice systems. University of Arizona researchers originally generated the concept space approach to facilitate sematic retrieval of information. User studies show that this system also improves searching and browsing in the engineering and biomedicine domains.

Hsinchun, C. (2007). Exploring extremism and terrorism on the web: The Dark Web project. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 4430 LNCS, 1-20.

Abstract:

In this paper we discuss technical issues regarding intelligence and security informatics (ISI) research to accomplish the critical missions of international security and counter-terrorism. We propose a research framework addressing the technical challenges facing counter-terrorism and crime-fighting applications with a primary focus on the knowledge discovery from databases (KDD) perspective. We also present several Dark Web related case studies for open-source terrorism information collection, analysis, and visualization. Using a web spidering approach, we have developed a large-scale, longitudinal collection of extremist-generated Internet-based multimedia and multilingual contents. We have also developed selected computational link analysis, content analysis, and authorship analysis techniques to analyze the Dark Web collection. © Springer-Verlag Berlin Heidelberg 2007.

Leroy, G., Chen, H., & Martinez, J. D. (2003). A shallow parser based on closed-class words to capture relations in biomedical text. Journal of Biomedical Informatics, 36(3), 145-158.

PMID: 14615225;Abstract:

Natural language processing for biomedical text currently focuses mostly on entity and relation extraction. These entities and relations are usually pre-specified entities, e.g., proteins, and pre-specified relations, e.g., inhibit relations. A shallow parser that captures the relations between noun phrases automatically from free text has been developed and evaluated. It uses heuristics and a noun phraser to capture entities of interest in the text. Cascaded finite state automata structure the relations between individual entities. The automata are based on closed-class English words and model generic relations not limited to specific words. The parser also recognizes coordinating conjunctions and captures negation in text, a feature usually ignored by others. Three cancer researchers evaluated 330 relations extracted from 26 abstracts of interest to them. There were 296 relations correctly extracted from the abstracts resulting in 90% precision of the relations and an average of 11 correct relations per abstract. © 2003 Elsevier Inc. All rights reserved.

Huang, Z., Chen, H., Xin, L. i., & Roco, M. C. (2006). Connecting NSF funding to patent innovation in nanotechnology (2001-2004). Journal of Nanoparticle Research, 8(6), 859-879.

Abstract:

Nanotechnology research has experienced growth rapid in knowledge and innovations; it also attracted significant public funding in recent years. Several countries have recognized nanotechnology as a critical research domain that promises to revolutionize a wide range of fields of applications. In this paper we present an analysis of the funding for nanoscale science and engineering (NSE) at the National Science Foundation (NSF) and its implications on technological innovation (number of patents) in this field from 2001 to 2004. Using a combination of basic bibliometric analysis and content visualization tools we identify growth trends research topic distribution and the evolution in NSF funding and commercial patenting activities recorded at the United States Patent Office (USPTO). The patent citations are used to compare the impact of the NSF-funded research on nanotechnology development with research supported by other sources in the United States and abroad. The analysis shows that the NSF-funded researchers and patents authored by them have significantly higher impact based on patent citation measures in the four-year period than other comparison groups. The NSF-authored patent impact is growing faster with the lifetime of a patent indicating the long-term importance of fundamental research. © Springer Science+Business Media Inc. 2006.

Jennifer, X. u., Chen, H., Zhou, Y., & Qin, J. (2006). On the topology of the dark web of terrorist groups. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 3975 LNCS, 367-376.

Abstract:

In recent years, terrorist groups have used the WWW to spread their ideologies, disseminate propaganda, and recruit members. Studying the terrorist websites may help us understand the characteristics of these websites and predict terrorist activities. In this paper, we propose to apply network topological analysis methods on systematically collected the terrorist website data and to study the structural characteristics at the Web page level. We conducted a case study using the methods on three collections of Middle-Eastern, US domestic, and Latin-American terrorist websites, We found that these three networks have the small-world and scale-free characteristics. We also found that smaller size websites which share same interests tend to make stronger inter-website linkage relationships. © Springer-Verlag Berlin Heidelberg 2006.