Publication statistics

Pub. period:2002-2007
Pub. count:13
Number of co-authors:30



Co-authors

Number of publications with 3 favourite co-authors:

Hsinchun Chen:12
Michael Chau:4
Wingyan Chung:4

 

 

Productive colleagues

Zan Huang's 3 most productive colleagues in number of publications:

Hsinchun Chen:145
Michael Chau:25
Wingyan Chung:20
 
 
 

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Zan Huang

 

Publications by Zan Huang (bibliography)

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2007
 
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Huang, Zan (2007): Selectively acquiring ratings for product recommendation. In: Gini, Maria L., Kauffman, Robert J., Sarppo, Donna, Dellarocas, Chrysanthos and Dignum, Frank (eds.) Proceedings of the 9th International Conference on Electronic Commerce - ICEC 2007 August 19-22, 2007, Minneapolis, MN, USA. pp. 379-388. Available online

2006
 
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Zheng, Rong, Li, Jiexun, Chen, Hsinchun and Huang, Zan (2006): A framework for authorship identification of online messages: Writing-style features and classification techniques. In JASIST - Journal of the American Society for Information Science and Technology, 57 (3) pp. 378-393. Available online

2004
 
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Huang, Zan, Chen, Hsinchun and Zeng, Daniel (2004): Applying associative retrieval techniques to alleviate the sparsity problem in collaborative filtering. In ACM Transactions on Information Systems, 22 (1) pp. 116-142. Available online

Recommender systems are being widely applied in many application settings to suggest products, services, and information items to potential consumers. Collaborative filtering, the most successful recommendation approach, makes recommendations based on past transactions and feedback from consumers sharing similar interests. A major problem limiting the usefulness of collaborative filtering is the sparsity problem, which refers to a situation in which transactional or feedback data is sparse and insufficient to identify similarities in consumer interests. In this article, we propose to deal with this sparsity problem by applying an associative retrieval framework and related spreading activation algorithms to explore transitive associations among consumers through their past transactions and feedback. Such transitive associations are a valuable source of information to help infer consumer interests and can be explored to deal with the sparsity problem. To evaluate the effectiveness of our approach, we have conducted an experimental study using a data set from an online bookstore. We experimented with three spreading activation algorithms including a constrained Leaky Capacitor algorithm, a branch-and-bound serial symbolic search algorithm, and a Hopfield net parallel relaxation search algorithm. These algorithms were compared with several collaborative filtering approaches that do not consider the transitive associations: a simple graph search approach, two variations of the user-based approach, and an item-based approach. Our experimental results indicate that spreading activation-based approaches significantly outperformed the other collaborative filtering methods as measured by recommendation precision, recall, the F-measure, and the rank score. We also observed the over-activation effect of the spreading activation approach, that is, incorporating transitive associations with past transactional data that is not sparse may "dilute" the data used to infer user preferences and lead to degradation in recommendation performance.

© All rights reserved Huang et al. and/or ACM Press

 
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Chung, Wingyan, Zhang, Yiwen, Huang, Zan, Wang, Gang, Ong, Thian-Huat and Chen, Hsinchun (2004): Internet searching and browsing in a multilingual world: An experiment on the Chinese Business Intelligence Portal (CBizPort). In JASIST - Journal of the American Society for Information Science and Technology, 55 (9) pp. 818-831. Available online

 
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Huang, Zan, Chung, Wingyan and Chen, Hsinchun (2004): A graph model for E-commerce recommender systems. In JASIST - Journal of the American Society for Information Science and Technology, 55 (3) pp. 259-274. Available online

 
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Huang, Zan, Chen, Hsinchun, Guo, Fei, Xu, Jennifer Jie, Wu, Soushan and Chen, Wun-Hwa (2004): Visualizing the Expertise Space. In: HICSS 2004 2004. . Available online

2003
 
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Zhou, Yilu, Qin, Jialun, Chen, Hsinchun, Huang, Zan, Zhang, Yiwen, Chung, Wingyan and Wang, Gang (2003): CMedPort: a cross-regional Chinese medical portal. In: JCDL03: Proceedings of the 3rd ACM/IEEE-CS Joint Conference on Digital Libraries 2003. p. 379. Available online

CMedPort is a cross-regional Chinese medical Web portal developed in the AI Lab at the University of Arizona. We will demonstrate the major system functionalities.

© All rights reserved Zhou et al. and/or ACM Press

 
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Qin, Jialun, Huang, Zan, Zhou, Yilu, Chau, Michael, Tseng, Chunju, Yip, Alan, Ng, T. Gavin, Guo, Fei, Chen, Zhi-Kai and Chen, Hsinchun (2003): NanoPort: an example for building knowledge portals for scientific domains. In: JCDL03: Proceedings of the 3rd ACM/IEEE-CS Joint Conference on Digital Libraries 2003. p. 387. Available online

We describe the NanoPort (www.nanoport.org) system to demonstrate a general framework of building domain-specific knowledge portals. These portals consolidate diverse information resources and provide rich functionalities to support effective information retrieval and knowledge discovery.

© All rights reserved Qin et al. and/or ACM Press

 
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Chen, Hsinchun, Zeng, Daniel, Kalla, Riyad, Huang, Zan, Cox, James C. and Swarthout, J. Todd (2003): EconPort: a digital library for Microeconomics education. In: JCDL03: Proceedings of the 3rd ACM/IEEE-CS Joint Conference on Digital Libraries 2003. p. 388. Available online

We present the EconPort system (www.econport.org), a digital library for Microeconomics education that incorporates experimental economics software and automated e-commerce agents.

© All rights reserved Chen et al. and/or ACM Press

 
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Chau, Michael, Huang, Zan and Chen, Hsinchun (2003): Teaching key topics in computer science and information systems through a web search engine project. In ACM Journal of Educational Resources in Computing, 3 (3) pp. 1-14. Available online

 
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Chen, Hsinchun, Atabakhsh, Homa, Petersen, Tim, Schroeder, Jennifer, Buetow, Ty, Chaboya, Luis G., O'Toole, Christopher D., Chau, Michael, Cushna, Tom, Casey, Dan and Huang, Zan (2003): COPLINK: Visualization for Crime Analysis. In: DG.O 2003 2003. . Available online

 
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Chen, Hsinchun, Atabakhsh, Homa, Petersen, Tim, Schroeder, Jennifer, Buetow, Ty, Chaboya, Luis G., O'Toole, Christopher D., Chau, Michael, Cushna, Tom, Casey, Dan and Huang, Zan (2003): COPLINK: Visualization for Crime Analysis. In: DG.O 2003 2003. . Available online

2002
 
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Huang, Zan, Chung, Wingyan, Ong, Thian-Huat and Chen, Hsinchun (2002): A graph-based recommender system for digital library. In: JCDL02: Proceedings of the 2nd ACM/IEEE-CS Joint Conference on Digital Libraries 2002. pp. 65-73. Available online

Research shows that recommendations comprise a valuable service for users of a digital library [11]. While most existing recommender systems rely either on a content-based approach or a collaborative approach to make recommendations, there is potential to improve recommendation quality by using a combination of both approaches (a hybrid approach). In this paper, we report how we tested the idea of using a graph-based recommender system that naturally combines the content-based and collaborative approaches. Due to the similarity between our problem and a concept retrieval task, a Hopfield net algorithm was used to exploit high-degree book-book, user-user and book-user associations. Sample hold-out testing and preliminary subject testing were conducted to evaluate the system, by which it was found that the system gained improvement with respect to both precision and recall by combining content-based and collaborative approaches. However, no significant improvement was observed by exploiting high-degree associations.

© All rights reserved Huang et al. and/or ACM Press

 
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