We introduce our participation of the TREC Relevance Feedback(RF) TRACK in 2009. The RF09 TRACK is focused on the explicit relevant feedback, where a few relevant and irrelevant documents are available to each query. Our system is implemented under the framework of probabilistic language model. We apply the constrained clustering on the top returned documents and extract the expanded words to r...

This paper presents a new method for controlling chaos in several classical chaotic Rössler systems using feedback control strategy. In particular, for an arbitrarily given equilibrium point of a Rössler system, we design explicit and simple feedback control laws by which the equilibrium point is globally and exponentially stabilized. Six typical Rössler systems are studied, and explicit formul...

Solutions to constrained linear model predictive control problems can be pre-computed off-line in an explicit form as a piecewise linear state feedback on a polyhedral partition of the state space, avoiding real-time optimization. We suggest an algorithm that will determine an approximate explicit piecewise linear state feedback by imposing an orthogonal search tree structure on the partition. ...

Prior computer-mediated group idea generation research has concluded that social loafing is likely an important factor in reducing individual and group task performance. Group researchers—both focusing on non-technology and technology-mediated groups—have theorized that loafing could be minimized if individuals and groups were given either clear feedback on their task performance or if given cl...

Visuomotor adaptation has been thought to be an implicit process that results when a sensory-prediction error signal is used to update a forward model. A striking feature of human competence is the ability to receive verbal instructions and employ strategies to solve tasks; such explicit processes could be used during visuomotor adaptation. Here, we used a novel task design that allowed us to o...

Collaborative filtering plays the key role in recent recommender systems. It uses a user-item preference matrix rated either explicitly (i.e., explicit rating) or implicitly (i.e., implicit feedback). Despite the explicit rating captures the preferences better, it often results in a severely sparse matrix. The paper presents a novel iterative semi-explicit rating method that extrapolates unrate...

Existing research in crowdsourcing has investigated how to recommend tasks to workers based on which task the workers have already completed, referred to as implicit feedback. We, on the other hand, investigate the task recommendation problem, where we leverage both implicit feedback and explicit features of the task. We assume that we are given a set of workers, a set of tasks, interactions (s...

Albeit the implicit feedback based recommendation problem— when only the user history is available but there are no ratings—is the most typical setting in real-world applications, it is much less researched than the explicit feedback case. State-of-the-art algorithms that are efficient on the explicit case cannot be straightforwardly transformed to the implicit case if scalability should be mai...