Recommender systems have evolved in the last years as specialized tools to assist users in a plethora of computermediated tasks by providing guidelines or hints. Most recommender ...
Abstract. Past evidence has shown that generic approaches to recommender systems based upon collaborative filtering tend to poorly scale. Moreover, their fitness for scenarios su...
Recommender systems are widely used to cope with the problem of information overload and, consequently, many recommendation methods have been developed. However, no one technique i...
Abstract. Critiquing is a powerful style of feedback for case-based recommender systems. Instead of providing detailed feature values, users indicate a directional preference for a...
James Reilly, Kevin McCarthy, Lorraine McGinty, Ba...
This paper presents a new technology for supporting flexible query management in recommender systems. It is aimed at guiding a user in refining her query when it fails to return ...
Conversational recommender systems help to guide users through a product-space towards a particular product that meets their specific requirements. During the course of a “conve...
Kevin McCarthy, James Reilly, Lorraine McGinty, Ba...
- Many software development platforms provide a large number of library components to make it easy to build high quality software. On the other hand, it became more and more diffic...
Recommender systems are a powerful tool for promoting sales in electronic commerce. An effective shopping recommender system can help boost the retailer’s sales by reminding cus...
Koung-Lung Lin, Jane Yung-jen Hsu, Han-Shen Huang,...
In this paper we discuss the Recommendz 1 recommender system. This domain-independent system combines the advantages of collaborative and content-based filtering in a novel way. ...
This paper focuses on question selection methods for conversational recommender systems. We consider a scenario, where given an initial user query, the recommender system may ask ...