Information Filtering systems learn user preferences either through explicit or implicit feedback. However, requiring users to explicitly rate items as part of the interface interaction can place a large burden on the user. Implicit feedback removes the burden of explicit user ratings by transparently monitoring user behavior such as time spent reading, mouse movement and scrolling behavior. Pr...

The goal of recommender systems is to make personalized product recommendations based on users’ taste. As the Netflix challenge demonstrated, one of the the most effective way to build such systems is through matrix factorization. Matrix factorization algorithms utilize prior product feedback given by users to automatically build user and product profiles. A product can then be recommended to a...

User modeling can be used in information filtering and retrieval systems to improve the representation of a user’s information needs. User models can be constructed by hand, or learned automatically based on feedback provided by the user about the relevance of documents that they have examined. By observing user behavior, it is possible to infer implicit feedback without requiring explicit rele...

Learning efficacy depends on its emotional context. The contents learned and the feedback received during training tinges this context. The objective here was to investigate the influence of content and feedback on the efficacy of implicit learning and to explore using functional imaging how these factors are processed in the brain. Twenty-one participants completed 150 trials of a probabilisti...

The nature of congestion feedback largely governs the behavior of congestion control. In datacenter networks, where RTTs are in hundreds of microseconds, accurate feedback is crucial to achieve both high utilization and low queueing delay. Proposals for datacenter congestion control predominantly leverage ECN or even explicit innetwork feedback (e.g., RCP-type feedback) to minimize the queuing ...

The purpose of this study is to investigate the effectiveness of response modes by item and feedback type in a webbased language learning program. The subjects of this study, 122 Korean tenth graders learning English as a foreign language, were placed into groups of four and were given a web-based language learning program consisting of two different varieties of item type (multiple choice and ...

In this paper, implicit controls are investigated for different classes of nonlinear systems, nonaffine systems in pure-feedback form and affine systems in strict-feedback form. While control system design for general unknown nonaffine nonlinear systems needs further investigation, elegant control designs are presented for known systems and systems with unknown scalar parametrization. Though fo...

The paper is concerned with the design and the evaluation of the combination of user interaction and informative content features for implicit and pseudo feedback-based document re-ranking. The features are observed during the visit of the top-ranked documents returned in response to a query. Experiments on a TREC Web test collection have been carried out and the experimental results are illust...

Humans consistently make predictions about the valence of future events and use feedback to validate initial predictions. While the valence of outcomes provides utilitarian information, the accuracy of predictions is crucial for future performance adjustment. The feedback related negativity (FRN), identified as a marker of reward prediction error, possibly encodes social rejection and social pr...