Feng Wang

According to our database1, Feng Wang authored at least 16 papers between 2012 and 2017.

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Bibliography

2017
Investigating users' eye movement behavior in critiquing-based recommender systems.
AI Commun., 2017

Explaining Recommendations Based on Feature Sentiments in Product Reviews.
Proceedings of the 22nd International Conference on Intelligent User Interfaces, 2017

2016
An Eye-Tracking Study: Implication to Implicit Critiquing Feedback Elicitation in Recommender Systems.
Proceedings of the 2016 Conference on User Modeling Adaptation and Personalization, 2016

Inferring Users' Critiquing Feedback on Recommendations from Eye Movements.
Proceedings of the Case-Based Reasoning Research and Development, 2016

A Nonlinear State Space Model for Identifying At-Risk Students in Open Online Courses.
Proceedings of the 9th International Conference on Educational Data Mining, 2016

Where to Place Your Next Restaurant?: Optimal Restaurant Placement via Leveraging User-Generated Reviews.
Proceedings of the 25th ACM International Conference on Information and Knowledge Management, 2016

2015
Review mining for estimating users' ratings and weights for product aspects.
Web Intelligence, 2015

Recommender systems based on user reviews: the state of the art.
User Model. User-Adapt. Interact., 2015

2014
Experiment on sentiment embedded comparison interface.
Knowl.-Based Syst., 2014

An intelligent market making strategy in algorithmic trading.
Frontiers Comput. Sci., 2014

Sentiment-enhanced explanation of product recommendations.
Proceedings of the 23rd International World Wide Web Conference, 2014

Collaborative Compound Critiquing.
Proceedings of the User Modeling, Adaptation, and Personalization, 2014

2013
Preference-based clustering reviews for augmenting e-commerce recommendation.
Knowl.-Based Syst., 2013

Recommendation for New Users with Partial Preferences by Integrating Product Reviews with Static Specifications.
Proceedings of the User Modeling, Adaptation, and Personalization, 2013

2012
Comparison of feature-level learning methods for mining online consumer reviews.
Expert Syst. Appl., 2012

Recommending Inexperienced Products via Learning from Consumer Reviews.
Proceedings of the 2012 IEEE/WIC/ACM International Conferences on Web Intelligence, 2012


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