J. Ben Schafer

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One of the potent personalization technologies powering the adaptive web is collaborative filtering. Collaborative filtering (CF) is the process of filtering or evaluating items through the opinions of other people. CF technology brings together the opinions of large interconnected communities on the web, supporting filtering of substantial quantities of(More)
Recommender systems are changing from novelties used by a few E-commerce sites, to serious business tools that are re-shaping the world of E-commerce. Many of the largest commerce Web sites are already using recommender systems to help their customers find products to purchase. A recommender system learns from a customer and recommends products that she(More)
Information filtering agents and collaborative filtering both attempt to alleviate information overload by identifying which items a user will find worthwhile. Information filtering (IF) focuses on the analysis of item content and the development of a personal user interest profile. Collaborative filtering (CF) focuses on identification of other users with(More)
Recommender systems are being used by an ever-increasing number of E-commerce sites to help consumers find products to purchase. What started as a novelty has turned into a serious business tool. Recommender systems use product knowledge—either hand-coded knowledge provided by experts or “mined” knowledge learned from the behavior of consumers—to guide(More)
Event-related fMRI was used to investigate the hypothesis that neural activity involved in response inhibition depends upon the nature of the response being inhibited. Two different Go/No-go tasks were compared-one with a high working memory load and one with low. The 'simple' Go/No-go task with low working memory load required subjects to push a button in(More)
A number of studies have used functional neuroimaging to examine the neural mechanisms of sentence comprehension; however, few fMRI studies have examined activation patterns associated with sentence comprehension after accounting for activation attributable to single-word-level tasks important for sentence comprehension. To investigate the patterns of(More)
In a world where the number of choices can be overwhelming, recommender systems help users find and evaluate items of interest. They do so by connecting users with information regarding the content of recommended items or the opinions of other individuals. Such systems have become powerful tools in domains such as electronic commerce, digital libraries, and(More)
BACKGROUND Attention-deficit/hyperactivity disorder (ADHD) has been shown to be associated with anomalous motor development, including excessive overflow movements. The neurological basis of these deficits has not been established. Functional magnetic resonance imaging (fMRI) was used to determine whether differences in brain activation during sequential(More)
Recommender systems are being used by an ever-increasing number of E-commerce sites to help consumers find products to purchase. What started as a novelty has turned into a serious business tool. Recommender systems use product knowledge – either hand-coded knowledge provided by experts or “mined” knowledge learned from the behavior of consumers – to guide(More)