Scholarly and Creative Activities Directory

Jianchao (Jack) Han, Ph.D.

Title: Assistant Professor, Computer Science

Department: Computer Science

Office: NSM A-133
Phone Extension: x2624
Email Username: jhan

Show All     Peer-Reviewed Books    Peer-Reviewed Chapters in Books    Peer-Reviewed Journal Articles    Peer-Reviewed Procedings of International Conferences    Grants Awarded    Awards and Honors    


Peer-Reviewed Books

  • Lin, T. Y., Han, J., A Special Issue on Granular Computing, International Journal of Intelligent System, Wiley Periodicals, Inc., 2008.
  • Lin, T. Y., Hu, X., Han, J., Shen, X., Li, Z.: Proceedings of 2007 IEEE International Conference on Granular Computing, the IEEE Computer Society Press, 2007, ISBN: 0-7695-3032-x.
  • Huang, S., Han, J., Management Expert Systems, Beijing University of Economics and Trade Press, 1995. (In Chinese)


 

Peer-Reviewed Chapters in Books

  • Han, J., Cercone, N., Principles and Perspectives of Granular Computing, Invited to appear in Encyclopedia of Complexity & System Science, ed. by Robert Meyers, Springer, 2008.
  • Han, J., Object-oriented Analysis and Design: A Granular Computing Approach, invited to appear in Novel Developments in Granular Computing: Applications for Advanced Human Reasoning and Soft Computation, ed. by Yao, J., IGI Global, Hershey, Pennsylvania, 2008.
  • Han, J. Lin, T. Y., Li, J., Cercone, N., Constructing Associative Classifiers from Decision Tables, Lecture notes in computer science 4482: 305-313, Springer, 2007.
  • Lin, T. Y., Han, J., High Frequent Value Reduct in Very Large Databases, Lecture notes in computer science 4482: 346-354, Springer, 2007.
  • Dong, J., Han, J., Class and Object, Encyclopedia of Computer Science and Engineering, Wah, B. (Ed.), John Wiley & Sons, Inc., June 2006.
  • Han, J., R. Sanchez, Hu, X., Feature Selection Based on Relative Attribute Dependency: An Experimental Study, Lecture Notes in Computer Science 3641: 214-223, 2005.
  • Han, J., Hu, X., Lin, T., Feature Subset Selection Based on Relative Dependency between Attributes, Lecture Notes in Computer Science 3066:176-185, 2004.
  • Han, J., Hu, X., Lin, T., An Efficient Algorithm for Computing Core Attributes in Database Systems, Lecture Notes in Computer Science 2871: 663-667, 2003
  • Han, J., Hu, X., Lin, T., A New Computation Model for Rough Set Theory Based on Database Systems, Lecture Notes in Computer Science 2737: 381-390, 2003.
  • Hu, X., Lin T., Han, J., A New Rough Set Model Based on Database Systems, Lecture Notes in Computer Science 2639: 114-121, 2003.
  • Han, J., Cercone, N., Hu, X. An Interactive Visualization System for Mining Association Rules, in Data Mining, Rough Sets and Granular Computing, T. Lin, Y. Yao, L. Zadeh (eds.), 145-165, Physica-Verlag, 2002.
  • Hu, X., Cercone, N., Han, J., Ziarko, W., GRS: A Generalized Rough Sets Model, in Data Mining, Rough Sets and Granular Computing, by T. Lin, Y. Yao, and L. Zadeh (Eds.), 447-460, Physica-Verlag, 2002.
  • Han, J., Cercone, N., Interactive Construction of Classification Rules, Lecture Notes in Computer Science 2336: 529-534, 2002.
  • Han, J., Cercone, N., Implementation Issues and Paradigms of Visual KDD Systems, Lecture Notes in Computer Science 2198: 454-463, 2001.
  • Han, J., Cercone, N., Interactive Construction of Decision Trees, Lecture Notes in Computer Science 2035, 575-580, 2001.
  • Han, J., Hu, X., Cercone, N., Supervised Learning: A Generalized Rough Set Approach, Lecture Notes in Computer Science 2005:322-329, 2000.
  • Han, J., An, A., Cercone, N., CViz: An Interactive Visualization System for Rule Induction, Lecture Notes in Computer Science 1822:214-226, 2000.
  • Han, J., Cercone, N., Typical Example Selection for Learning Classifiers, Lecture Notes in Computer Science 1822:347-356, 2000.
  • Han, J., Cercone, N., AVIZ: A Visualization System for Discovering Numerical Association Rules, Lecture Notes in Computer Science 1805: 269-280, 2000.
  • Han, J., Cercone, N., DVIZ: A Visualization System for Data Mining, Lecture Notes in Computer Science 1574: 390-399, 1999.
  • Han, J., Shi, Z., Attribute-based algorithm of learning by analogy, New Generation Computing: Recent Research, Ci, Y., et al (Eds.) Qsinghua University Press, 1990.


 

Peer-Reviewed Journal Articles

  • Lin, T. Y., Han, J., Granular Computing: Models and Applications, to appear in International Journal of Intelligent Systems, manuscript accepted in a special issue.
  • Han, J., A Study on Feature Subset Selection Using Rough Set Theory, manuscript accepted to Journal of Approximate Reasoning.
  • Han, J., Beheshti, M., An Iterative Approach for Fuzzy Clustering based on Feature Significance, Journal of Advanced Computational Intelligence and Intelligent Informatics 11 (10), 2008.
  • Han, J., Beheshti, M., Kowalski, K., Detecting Network Intrusions Based on a Generalized Rough Set Model, The Mediterranean Journal on Computer and Networks 3(3): 72-79, 2007.
  • Han, J., Beheshti, M., Discovering Both Positive and Negative Fuzzy Association Rules in Large Transaction Databases, Journal of Advanced Computational Intelligence and Intelligent Informatics 10(3):287-294, 2006.
  • Hu, X., Lin, T., Han, J., A New Rough Sets Model Based on Database Systems, Journal of Fundamenta Informaticae 59(2-3):135-152, 2004.
  • Han, J., Hu, X., Cercone, N., A visualization model of interactive knowledge discovery systems and its implementations, Journal of Information Visualization 2(2):105-125, 2003, Palgrave Macmillan.
  • Han, J. Using Table Lens to Interactively Build Classifiers, Applied Mathematics Letters 14:663-666, Elsevier Science Ltd., Pergamon, 2001.
  • Han, J., Cercone, N. Visualizing the Process of Knowledge Discovery, Journal of Electronic Imaging, SPIE, 9(4):404-420, 2000.
  • Han, J., Shi, Z., Formalizing default reasoning, International Journal of Computer Science and Technology 5(4): 374-378, 1991.
  • Han, J., Shi, Z., AIKAS—Attribute-based Inductive Knowledge Acquisition System, ACTA Electronica Sinica 18(2):1-12, 1991.
  • Shi, Z., Han, J., Attribute theory in learning systems, Future Generation Computer Systems 6:267-272, Elsevier Science Publishers, North Holland, 1990.
  • Han, J., The limits of deductive logic in knowledge engineering, Journal of computer aided engineering, No.4, 1995. (In Chinese).
  • Han, J., Information systems integration, Journal of information system and engineering, No.11, 1994. (In Chinese)
  • Han, J., Huang, J., A fourth generation language: ACCELL, Journal of Information and Computer, No.4, 1993. (In Chinese)
  • Han, J. Knowledge acquisition and machine learning, Chinese Computer Users, 10(2), 1992. (In Chinese)
  • Han, J., Zhang, R., Weather forecast expert system for Yueyang City, Journal of Computer Research and Development, No.11, 1992. (In Chinese)
  • Han, J., On Inductive Machine Learning, Journal of Computer Science, No. 6, 1991. (In Chinese).
  • Han, J., Zhang, R., An Petroleum Expert System for Daqing Oil Field, Journal of Computer Science and Development, No. 11, 1991. (In Chinese)
  • Han, J., Shi, Z., Learning by similarity, Journal of Computer Engineering and Applications, No. 3, 1990. (In Chinese)
  • Han, J., Inductive Learning and Default Reasoning, Journal of Microelectronics and Computer, No. 6, 1989. (In Chinese)


 

Peer-Reviewed Procedings of International Conferences

  • Han, J., Dong, J., Perspectives of Granular Computing in Software Engineering, in Proc. of IEEE International Conf. on Granular Computing, pp.66-71, IEEE Publishers, Nov., 2007, Fremont, California.
  • Li, J., Cercone, N., Han, J., A Method of Finding Representative Sets of Rules, in Proc. of IEEE International Conf. on Granular Computing, pp.330-335, IEEE Publishers, Nov. 2007, Fremont, California.
  • Han, J., Beheshti, M., Kowalski, K., A Fast Feature Selection Approach for Network Intrusion Detection Systems, Proc. of International Conference on Electrical Engineering, Iran, May 13-15, 2007.
  • Beheshti, M., Trang, T., Kowalski, K., Han, J., Student Advising System, Proc. of World Conference on E-Learning, 2727-2731, Honolulu, Hawaii, October 13-17, 2006.
  • Han, J., Learning Fuzzy Association Rules and Associative Classification Rules, Proc. of IEEE International Conference on Fuzzy Systems: 7225-7230, July 16-21, 2006, Vancouver, British Columbia, Canada.
  • Beheshti, M., Han, J., Longpre, L., Starks, S., Vargas, J., Xiang, G., Interval and Fuzzy Techniques in Business-Related Computer Security: Intrusion Detection, Privacy Protection, The Proc. of the 2nd International Conference on Fuzzy Sets and Soft Computing in Economics and Finance: 23-29, June 28-July 1, 2006, Saint-Petersburg, Russia.
  • Han, J., Beheshti, M., Mining Fuzzy Association Rules: Interestingness Measure and Algorithm, Proc. of the 2nd IEEE International Conference on Granular Computing: 659-662, May 10-12, Atlanta, Georgia, USA.
  • Han, J., Anomaly Detection Based on a Rough Set Approach, The 4th Information Technology and Network Security Conference, March 21-24, 2006, Anaheim, California, USA.
  • Han, J., M. Beheshti, An Approach for Fuzzy Clustering with Feature Significance, The 6th International Conference on Intelligent Technologies, December, 14-16, 2005, Phuket, Thailand.
  • Kowalski, K., Beheshti, M., Han, J., Autonomous On-line Advising, Proc. of World Conference on E-Learning (1):836-843, October 24-28, 2005, Vancouver, Canada.
  • Han, J., Kowalski, K., Beheshti, M., Detecting Network Intrusions Based on a Generalized Rough Set Model, Proc. of International Symposium on Telecommunications I, 247-252, September 10-12, 2005, Shiraz, Iran.
  • Han, J., Feature Selection Based on Rough Set and Information Entropy, Proc. of IEEE Internal. Conf. on Granular Computing, July 25-27, 2005, Beijing, China.
  • Han, J., Integrating Relational Operations with Rough Set Theory to Select Feature Subsets, Proc. of the 9th World Multiconference on Systemics, Cybernetics and Informatics, July 10-13, 2005, Orlando, Florida, USA.
  • Han, J., Beheshti, M., Discovering Both Positive and Negative Fuzzy Association Rules in Databases, Proceedings of International Conference on Intelligent Technology, December 2-4, 2004, Houston, Texas.
  • Sanchez, R., Han, J., Feature Selection with Relative Attribute Dependency: Algorithms and Implementation, Proceedings of International Conference on Intelligent Technology, December 2-4, 2004, Houston, Texas.
  • Hu, X., Yoo, I., Song, I., Song, M., Han, J., Lechner, M., Extracting and Mining Protein-Protein Interaction Network from Biomedical Literature, Proc. of IEEE International Symposium on Computational Intelligence in Bioinformatics and Computational Biology, 244-251, October 7-8, 2004, La Jolla, California.
  • Han, J., Cercone, N., Hu, X., A Weighted Freshness Metric for Maintaining Search Engine Local Repository, Proc. of the IEEE/WIC/ACM International Conference on Web Intelligence, 677-680, Sept. 20-24, 2004, Beijing, China.
  • Lin, T., Cercone, N., Xiaohua Hu, Han, J., Intelligent query answering based on neighborhood systems and data mining techniques, Proc. of 8th IEEE International Database Engineering and Applications Symposium (IDEAS), 91-96, July 7-9, 2004, Coimbra, Portugal.
  • Hu, X., Lin, T., Han, J., Cercone, N., Yoo, I., Feature Clustering for Genomic Data Analysis, Proc. of IEEE International Workshop on Foundation and New Direction in Data Mining, November 19-22, 2003, Melbourne, Florida.
  • Han, J., Hu, X., Cercone, N. On Graph-based Methods for Inferring Web Communities, Proc. of Workshop on Applications, Products and Services of Web-based Support Systems, 145-152, October 13-16, 2003, Halifax, Canada.
  • Hu, X., Han, J., Cercone, N., Discovering Cyber Communities from the WWW, Proc. of the 27th Annual International Computer Software and Applications Conference, 590-594, Nov. 3-6, 2003, Dallas, Texas.
  • Hu, X., Han, J., Discovering Clusters from Large Scale-Free Network Graph, Proc. of ACM SIGKDD Fractal, Power Laws and Next Data Mining Tool Workshop, Aug 27-29, 2003, Washington DC.
  • Han, J., Hu, X., Cercone, N., Interactive Visual KDD: Model and Implementation, Proc. of International Workshop on the Foundation of Data Mining, December 9-12, 2002, Maebashi, Japan.
  • Han, J., Cercone, N., RuleViz: A Model for Visualizing Knowledge Discovery Process, Proc. of International Conf. on Knowledge Discovery and Data Mining, 244-253, 2000, Boston, Massachusetts, ACM SIGKDD.
  • Han, J., Shi, Z., Attribute-based fuzzy conceptual clustering, Proc. of 2nd Int. Conf. for Young Computer Scientists, 446-449, August 1991, Beijing, China, International Academic Publishers.
  • Han, J., A model of inductive learning based on attribute, Proc. of Int. Conf. on Expert Systems in Engineering Application, 98-101, September 1989, Wuhan, China, International Academic Publishers.
  • Han, J., An Algorithm of Learning by Analogy Based on Attribute, Proc. of 1st Int. Symposium for Young Computer Professionals, 632-636, July 1989, Beijing, China, International Academic Publishers.
  • Han, J., Non-monotonic reasoning based on possibility, Proc. of 1st Int. Symposium for Young Computer Professionals, 628-631, July 1989, Beijing, China, International Academic Publishers.
  • Han, J., Shi, Z., Using interval-valued fuzzy sets to formalize default reasoning, Proc. of the IEEE International Conf. on Systems, Man and Cybernetics, Vol. 1, 167-169, August 1988, Beijing, China, International Academic Publishers.
  • Han, J., Shi. Z., Robot planning by analogy, Proc. of the IEEE Int. Conf. on Systems, Man and Cybernetics, Vol.2, 781-784, August 1988, Beijing, China, International Academic Publishers.


 

Grants Awarded

  • Research Advisor and PLTL Faculty Advisor of a grant: Broadening Participation in Computing (BPC) –Computing Alliance of Hispanic Serving Institutions (CASHI), sponsored by Natural Science Foundation (NSF). (2006-2008)
  • Research Coordinator of a grant: Intrusion Detection Systems Using Sensors and Data Fusion, sponsored by Department of Defense (DoD) – National Geospacial Intelligence Agency (NGA). (2006-2009)
  • CSUDH CTL Mini-grant for conference travel (Spring 2007): $500
  • CSUPERB Faculty-Student Collaborative Research Seed Grant (2006-2007): $10,000
  • CSUDH- Sally Casanova Memorial RSCAAP Summer Fellowship (2005): $2250
  • California State University Pre-Doctor Program Mentor’s Travel Grant (2005): $1000
  • CSU Program for Education and Research in Biotechnology (CSUPERB) Fall 2004 Travel Grant (2004): $1000
  • CSUDH- Sally Casanova Memorial RSCAAP Summer Fellowship (2004): $4500
  • CAS-CSUDH Fund for Faculty Excellence (2003): $1200


 

Awards and Honors

  • Best Overall Paper Award: Extracting and Mining Protein-Protein Interaction Network from Biomedical Literature, with Hu, X., Yoo, I., Song, I., Song, M., and Lechner, M., IEEE International Symposium on Computational Intelligence in Bioinformatics and Computational Biology, October 7-8, 2004, La Jolla, California.
  • Best Paper Award: CViz: An Interactive Visualization System for Rule Induction, with An, A. and Cercone, N., 13th Biennial Conference of the Canadian Society for Computational Studies of Intelligence, May 14-17, 2000, Montréal, Canada.
  • Student Travel Award: RuleViz: A Model for Visualizing Knowledge Discovery Process, International. Conference on Knowledge Discovery and Data Mining, August, 20-24, 2000, Boston, USA.
  • Best Paper Award: A model of inductive learning based on attributes, International Conference on Expert Systems in Engineering Application, September 20-23, 1989, Wuhan, China.


 

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