The scientist’s investigation covers issues in Recommender system, Human–computer interaction, Knowledge management, Decision support system and Preference elicitation. Many of her studies on Recommender system apply to Personality as well. Her studies in Human–computer interaction integrate themes in fields like World Wide Web and Product.
Her Knowledge management research incorporates elements of User experience design, Cognitive effort and Internet privacy. Her biological study deals with issues like Consistency, which deal with fields such as Quality and Usability. Her work carried out in the field of Decision support system brings together such families of science as Range, Outcome and Order.
Pearl Pu spends much of her time researching Recommender system, Human–computer interaction, World Wide Web, Artificial intelligence and Knowledge management. In her works, she conducts interdisciplinary research on Recommender system and Preference elicitation. Her work deals with themes such as E-commerce, Decision support system, Dialog box and Set, which intersect with Human–computer interaction.
Her work in World Wide Web is not limited to one particular discipline; it also encompasses User modeling. Her Artificial intelligence research is multidisciplinary, relying on both Machine learning, Computer vision and Natural language processing. Many of her studies involve connections with topics such as Quality and Usability.
Pearl Pu focuses on Behavior change, Human–computer interaction, Artificial intelligence, Applied psychology and Dialog box. Pearl Pu integrates Human–computer interaction with Constructive in her research. The concepts of her Artificial intelligence study are interwoven with issues in Machine learning and Natural language processing.
Her study in Dialog box is interdisciplinary in nature, drawing from both Quality and Natural language. Her Natural language research includes elements of Surprise and World Wide Web. Her Set research incorporates elements of Structure and Eye movement.
Pearl Pu mainly focuses on Internet privacy, Gerontology, Strong ties, Behavior change and Competition. Her research integrates issues of Multimedia and Competence in her study of Internet privacy. Her Physical exercise research extends to the thematically linked field of Gerontology.
Her Strong ties research includes elements of Social relationship, Baseline, Social psychology, Work and Online community. Many of her studies on Behavior change involve topics that are commonly interrelated, such as Set.
This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.
A user-centric evaluation framework for recommender systems
Pearl Pu;Li Chen;Rong Hu.
conference on recommender systems (2011)
Evaluating recommender systems from the user's perspective: survey of the state of the art
Pearl Pu;Li Chen;Rong Hu.
User Modeling and User-adapted Interaction (2012)
Trust building with explanation interfaces
Pearl Pu;Li Chen.
intelligent user interfaces (2006)
Survey of Preference Elicitation Methods
Li Chen;Pearl Pu.
(2004)
Critiquing-based recommenders: survey and emerging trends
Li Chen;Pearl Pu.
User Modeling and User-adapted Interaction (2012)
Trust-inspiring explanation interfaces for recommender systems
Pearl Pu;Li Chen.
Knowledge Based Systems (2007)
Issues and Applications of Case Based Reasoning to Design
Mary Lou Maher;Pearl Pu.
Issues and Applications of Case Based Reasoning to Design (1997)
Enhancing collaborative filtering systems with personality information
Rong Hu;Pearl Pu.
conference on recommender systems (2011)
HealthyTogether: exploring social incentives for mobile fitness applications
Yu Chen;Pearl Pu.
Proceedings of the Second International Symposium of Chinese CHI on (2014)
Acceptance issues of personality-based recommender systems
Rong Hu;Pearl Pu.
conference on recommender systems (2009)
Profile was last updated on December 6th, 2021.
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