Abstract We study optimal pricing in the presence of recommender systems. A recommender system affects the market in two ways: (i) it creates value by reducing product uncertaint...
In the context of electronic commerce, recommender systems enable merchants to assist customers in finding available products that will best satisfy their need. However, a recomm...
Abstract. A good way to help users finding relevant items on document platforms consists in suggesting content in accordance with their preferences. When implementing such a recom...
Abstract. Recommender systems produce social networks as a side effect of predicting what users will like. However, the potential for these social networks to aid in recommending i...
Recommender systems apply knowledge discovery techniques to help in finding associated information. In this paper, we investigate the use of association rule mining as an underlyi...
Recommender systems based on collaborative filtering predict user preferences for products or services by learning past user-item relationships. A predominant approach to collabo...
The information explosion in today’s electronic world has created the need for information filtering techniques that help users filter out extraneous content to identify the righ...
Kannan Chandrasekaran, Susan Gauch, Praveen Lakkar...
A common task of recommender systems is to improve customer experience through personalized recommendations based on prior implicit feedback. These systems passively track differe...
We describe a recommender system based on Dynamically Structured Holographic Memory (DSHM), a cognitive model of associative memory that uses holographic reduced representations a...
Matthew Rutledge-Taylor, Andre Vellino, Robert L. ...
We explore the use of modern recommender system technology to address the problem of learning software applications. Before describing our new command recommender system, we first...
Justin Matejka, Wei Li, Tovi Grossman, George W. F...