Publication statistics

Pub. period:1999-2011
Pub. count:19
Number of co-authors:20


Number of publications with 3 favourite co-authors:

Rong Hu:
Qunsheng Peng:
Jianguo Ying:



Productive colleagues

Li Chen's 3 most productive colleagues in number of publications:

Qunsheng Peng:68
Hujun Bao:43
Elke A. Rundenstei..:36

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Li Chen


Publications by Li Chen (bibliography)

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Pu, Pearl, Chen, Li and Hu, Rong (2011): A user-centric evaluation framework for recommender systems. In: Proceedings of the 2011 ACM Conference on Recommender Systems 2011. pp. 157-164.

This research was motivated by our interest in understanding the criteria for measuring the success of a recommender system from users' point view. Even though existing work has suggested a wide range of criteria, the consistency and validity of the combined criteria have not been tested. In this paper, we describe a unifying evaluation framework, called ResQue (Recommender systems' Quality of user experience), which aimed at measuring the qualities of the recommended items, the system's usability, usefulness, interface and interaction qualities, users' satisfaction with the systems, and the influence of these qualities on users' behavioral intentions, including their intention to purchase the products recommended to them and return to the system. We also show the results of applying psychometric methods to validate the combined criteria using data collected from a large user survey. The outcomes of the validation are able to 1) support the consistency, validity and reliability of the selected criteria; and 2) explain the quality of user experience and the key determinants motivating users to adopt the recommender technology. The final model consists of thirty two questions and fifteen constructs, defining the essential qualities of an effective and satisfying recommender system, as well as providing practitioners and scholars with a cost-effective way to evaluate the success of a recommender system and identify important areas in which to invest development resources.

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

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Yuan, Quan, Chen, Li and Zhao, Shiwan (2011): Factorization vs. regularization: fusing heterogeneous social relationships in top-n recommendation. In: Proceedings of the 2011 ACM Conference on Recommender Systems 2011. pp. 245-252.

Collaborative Filtering (CF) based recommender systems often suffer from the sparsity problem, particularly for new and inactive users when they use the system. The emerging trend of social networking sites and their accommodation in other sites like e-commerce can potentially help alleviate the sparsity problem with their provided social relation data. In this paper, we have particularly explored a new kind of social relation, the membership, and its combined effect with friendship. The two type of heterogeneous social relations are fused into the CF recommender via a factorization process. Due to the two relations' respective properties, we adopt different fusion strategies: regularization was leveraged for friendship and collective matrix factorization (CMF) was proposed for incorporating membership. We further developed a unified model to combine the two relations together and tested it with real large-scale datasets at five sparsity levels. The experiment has not only revealed the significant effect of the two relations, especially the membership, in augmenting recommendation accuracy in the sparse data condition, but also identified the ability of our fusing model in achieving the desired fusion performance.

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

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Felfernig, Alexander, Chen, Li and Mandl, Monika (2011): RecSys'11 workshop on human decision making in recommender systems. In: Proceedings of the 2011 ACM Conference on Recommender Systems 2011. pp. 389-390.

Interacting with a recommender system means to take different decisions such as selecting a song/movie from a recommendation list, selecting specific feature values (e.g., camera's size, zoom) as criteria, selecting feedback features to be critiqued in a critiquing based recommendation session, or selecting a repair proposal for inconsistent user preferences when interacting with a knowledge-based recommender. In all these scenarios, users have to solve a decision task. The major focuses of this workshop (Decisions@RecSys) were approaches for efficient human decision making in different types of recommendation scenarios.

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

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Chen, Li (2010): Social influence of product popularity on consumer decisions: usability study of Flickr camera finder. In: Proceedings of the 2010 International Conference on Intelligent User Interfaces 2010. pp. 297-300.

"Product popularity" is in-depth explored in this paper, regarding its practical role within a consumer's decision process. Specifically, the usability evaluation of a novel product finder service (Flickr Camera Finder) shows that users more frequently consulted it, rather than a standard shopping site, to locate popular products. User comments further revealed their credibility concerns and tendency to trust the "popularity" from social resources. Design implications from the experiment are summarized at the end, indicating suggestive directions to integrate social media data to boost current e-commerce decision tools.

© All rights reserved Chen and/or his/her publisher

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Guy, Ido, Chen, Li and Zhou, Michelle X. (2010): Workshop on social recommender systems. In: Proceedings of the 2010 International Conference on Intelligent User Interfaces 2010. pp. 433-434.

This workshop brought researchers from academia and industry together to share recent advances and discuss research directions for recommender systems in social media and Web 2.0. With social media sites becoming ubiquitous, the challenges and opportunities for recommendation technologies become greater, setting the grounds for new research and innovation.

© All rights reserved Guy et al. and/or their publisher

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Chen, Li and Pu, Pearl (2010): Experiments on the preference-based organization interface in recommender systems. In ACM Transactions on Computer-Human Interaction, 17 (1) p. 5.

As e-commerce has evolved into its second generation, where the available products are becoming more complex and their abundance is almost unlimited, the task of locating a desired choice has become too difficult for the average user. Therefore, more effort has been made in recent years to develop recommender systems that recommend products or services to users so as to assist in their decision-making process. In this article, we describe crucial experimental results about a novel recommender technology, called the preference-based organization (Pref-ORG), which generates critique suggestions in addition to recommendations according to users' preferences. The critique is a form of feedback ("I would like something cheaper than this one") that users can provide to the currently displayed product, with which the system may better predict what the user truly wants. We compare the preference-based organization technique with related approaches, including the ones that also produce critique candidates, but without the consideration of user preferences. A simulation setup is first presented, that identified Pref-ORG's significantly higher algorithm accuracy in predicting critiques and choices that users should intend to make, followed by a real-user evaluation which practically verified its significant impact on saving users' decision effort.

© All rights reserved Chen and Pu and/or ACM Press

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Chen, Li and Pu, Pearl (2010): Eye-Tracking Study of User Behavior in Recommender Interfaces. In: Proceedings of the 2010 Conference on User Modeling, Adaptation and Personalization 2010. pp. 375-380.

Recommender systems, as a type of Web personalized service to support users' online product searching, have been widely developed in recent years but with primary emphasis on algorithm accuracy. In this paper, we particularly investigate the efficacy of recommender interface designs in affecting users' decision making strategies through the observation of their eye movements and product selection behavior. One interface design is the standard list interface where all recommended items are listed one by one. Another two are layout variations of organization-based interface where recommendations are grouped into categories. The eye-tracking user evaluation shows that the organization interfaces, especially the one with a quadrant layout, can significantly attract users' attentions to more items, with the resulting benefit to enhance their objective decision quality.

© All rights reserved Chen and Pu and/or their publisher

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Chen, Li (2009): Adaptive tradeoff explanations in conversational recommenders. In: Proceedings of the 2009 ACM Conference on Recommender Systems 2009. pp. 225-228.

The completeness and certainty of a user's preferences may vary during her preference construction process in a conversational recommender. In order to more effectively support users to uncover their hidden criteria and/or solve preference conflicts, we propose to generate adaptive tradeoff explanations in organization-based recommender interfaces, to be conditional on the user's contextual needs. An experiment shows the adaptive element's higher potential to improve recommendation efficiency, relative to methods without this feature.

© All rights reserved Chen and/or ACM Press

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Jones, Nicolas, Pu, Pearl and Chen, Li (2009): How Users Perceive and Appraise Personalized Recommendations. In: Proceedings of the 2009 Conference on User Modeling, Adaptation and Personalization 2009. pp. 461-466.

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Chen, Li and Pu, Pearl (2008): A cross-cultural user evaluation of product recommender interfaces. In: Proceedings of the 2008 ACM Conference on Recommender Systems 2008. pp. 75-82.

We present a cross-cultural user evaluation of an organization-based product recommender interface, by comparing it with the traditional list view. The results show that it performed significantly better, for all study participants, in improving on their competence perceptions, including perceived recommendation quality, perceived ease of use and perceived usefulness, and positively impacting users' behavioral intentions such as intention to save effort in the next visit. Additionally, oriental users were observed reacting more significantly strongly to the organization interface regarding some subjective aspects, compared to western subjects. Through this user study, we also identified the dominating role of the recommender system's decision-aiding competence in stimulating both oriental and western users' return intention to an e-commerce website where the system is applied.

© All rights reserved Chen and Pu and/or ACM Press

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Chen, Li and Pu, Pearl (2007): Hybrid critiquing-based recommender systems. In: Proceedings of the 2007 International Conference on Intelligent User Interfaces 2007. pp. 22-31.

We propose a novel critiquing-based recommender interface, the hybrid critiquing interface that integrates the user self-motivated critiquing facility to compensate for the limitations of system-proposed critiques. The results from our user study show that the integration of such self-motivated critiquing support enables users to achieve a higher level of decision accuracy while consuming less cognitive effort. In addition, users expressed higher subjective opinions of the hybrid critiquing interface than the interface simply providing system-proposed critiques, and they would more likely return to it for future use.

© All rights reserved Chen and Pu and/or ACM Press

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Chen, Li and Pu, Pearl (2007): Preference-Based Organization Interfaces: Aiding User Critiques in Recommender Systems. In: Conati, Cristina, McCoy, Kathleen F. and Paliouras, Georgios (eds.) User Modeling 2007 - 11th International Conference - UM 2007 June 25-29, 2007, Corfu, Greece. pp. 77-86.

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Chen, Li and Pu, Pearl (2007): The evaluation of a hybrid critiquing system with preference-based recommendations organization. In: Proceedings of the 2007 ACM Conference on Recommender Systems 2007. pp. 169-172.

The critiquing-based recommender system mainly aims to guide users to make an accurate and confident decision, while requiring them to consume a low level of effort. We have previously found that the hybrid critiquing system of combining the strengths from both system-proposed critiques and user self-motivated critiquing facility can highly improve users' subjective perceptions such as their decision confidence and trusting intentions. In this paper, we continue to investigate how to further reduce users' objective decision effort (e.g. time consumption) in such system by increasing the critique prediction accuracy of the system-proposed critiques. By means of real user evaluation, we proved that a new hybrid critiquing system design that integrates the preference-based recommendations organization technique for critiques suggestion can effectively help to increase the proposed critiques' application frequency and significantly contribute to saving users' task time and interaction effort.

© All rights reserved Chen and Pu and/or ACM Press

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Pu, Pearl and Chen, Li (2006): Trust building with explanation interfaces. In: Proceedings of the 2006 International Conference on Intelligent User Interfaces 2006. pp. 93-100.

Based on our recent work on the development of a trust model for recommender agents and a qualitative survey, we explore the potential of building users' trust with explanation interfaces. We present the major results from the survey, which provided a roadmap identifying the most promising areas for investigating design issues for trust-inducing interfaces. We then describe a set of general principles derived from an in-depth examination of various design dimensions for constructing explanation interfaces, which most contribute to trust formation. We present results of a significant-scale user study, which indicate that the organization-based explanation is highly effective in building users' trust in the recommendation interface, with the benefit of increasing users' intention to return to the agent and save cognitive effort.

© All rights reserved Pu and Chen and/or ACM Press

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Sun, Delin, Wang, Xiaoling, Chen, Li and Sun, An (2005): Research on the training mode of compound professionals on informationalization-based business in universities of China. In: Li, Qi and Liang, Ting-Peng (eds.) Proceedings of the 7th International Conference on Electronic Commerce - ICEC 2005 August 15-17, 2005, Xian, China. pp. 780-783.

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Chen, Li and Wang, Jia (2005): An improved QTCQ wavelet image coding method using DCT and coefficient reorganization. In: Zhang, Hongjiang, Chua, Tat-Seng, Steinmetz, Ralf, Kankanhalli, Mohan S. and Wilcox, Lynn (eds.) Proceedings of the 13th ACM International Conference on Multimedia November 6-11, 2005, Singapore. pp. 511-514.

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Chen, Li and Rundensteiner, Elke A. (2005): XQuery containment in presence of variable binding dependencies. In: Proceedings of the 2005 International Conference on the World Wide Web 2005. pp. 288-297.

Semantic caching is an important technology for improving the response time of future user queries specified over remote servers. This paper deals with the fundamental query containment problem in an XQuery-based semantic caching system. To our best knowledge, the impact of subtle differences in XQuery semantics caused by different ways of specifying variables on query containment has not yet been studied. We introduce the concept of variable binding dependencies for representing the hierarchical element dependencies preserved by an XQuery. We analyze the problem of XQuery containment in the presence of such dependencies. We propose a containment mapping technique for nested XQuery in presence of variable binding dependencies. The implication of the nested block structure on XQuery containment is also considered. We mention the performance gains achieved by a semantic caching system we build based on the proposed technique.

© All rights reserved Chen and Rundensteiner and/or ACM Press

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Suzuki, Yasuko, Fujishiro, Issei, Chen, Li and Nakamura, Hiroko (2002): Case Study: Hardware-Accelerated Selective LIC Volume Rendering. In: IEEE Visualization 2002 2002. .

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Bao, Hujun, Chen, Li, Ying, Jianguo and Peng, Qunsheng (1999): Non-linear view interpolation. In Journal of Visualization and Computer Animation, 10 (4) pp. 233-241.

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