Recommender systems are currently an ubiquitous presence on the web, helping us find relevant items in the ever-growing plethora of information available. However, there is not a one-size fits-all for recommender systems, and flexibility and control are crucial for enabling the possibility of adapting the recommender system to different user preferences. In this paper, we present the results of a study designed to assess user interaction with IntersectionExplorer (IEx), a multi-perspective tool for exploring conference paper recommendations. The study was conducted at the Digital Humanities 2016 Conference, an event with a rather large, heterogeneous, and not technology-oriented audience. The results obtained indicate that the IEx multi-per...
Offering diversity in the output of a recommender system is an active research question. Most of the...
Recommender systems for news articles on social media select and filter content through automatic pe...
Research on recommender systems has traditionally focused on the development of algorithms to improv...
In this paper, we advent a novel approach to foster exploration of recommendations: IntersectionExpl...
Recent efforts in recommender systems research focus increasingly on human factors affecting recomme...
Several approaches have been researched to help people deal with abundance of information. An import...
Several approaches have been researched to help people deal with abundance of information. An import...
Several approaches have been researched to help people deal with abundance of information. An import...
Previous research on diversity in recommender systems define diversity as the opposite of similarity...
Diversity in personalized news recommender systems is often defined as dissimilarity, and operationa...
© 2016 ACM 2160-6455/2016/07-ART11 $15.00. Several approaches have been researched to help people de...
Recommender systems are the backbones of a variety of critical services provided by tech-heavy appli...
The beyond-relevance objectives of recommender systems have been drawing more and more attention. Fo...
In this demo, we showcase a novel mobile application that offers various ways to present recommendat...
The 11th ACM Conference on Recommender Systems, Como, Italy, 27-31 August 2017Many state-of-the-art ...
Offering diversity in the output of a recommender system is an active research question. Most of the...
Recommender systems for news articles on social media select and filter content through automatic pe...
Research on recommender systems has traditionally focused on the development of algorithms to improv...
In this paper, we advent a novel approach to foster exploration of recommendations: IntersectionExpl...
Recent efforts in recommender systems research focus increasingly on human factors affecting recomme...
Several approaches have been researched to help people deal with abundance of information. An import...
Several approaches have been researched to help people deal with abundance of information. An import...
Several approaches have been researched to help people deal with abundance of information. An import...
Previous research on diversity in recommender systems define diversity as the opposite of similarity...
Diversity in personalized news recommender systems is often defined as dissimilarity, and operationa...
© 2016 ACM 2160-6455/2016/07-ART11 $15.00. Several approaches have been researched to help people de...
Recommender systems are the backbones of a variety of critical services provided by tech-heavy appli...
The beyond-relevance objectives of recommender systems have been drawing more and more attention. Fo...
In this demo, we showcase a novel mobile application that offers various ways to present recommendat...
The 11th ACM Conference on Recommender Systems, Como, Italy, 27-31 August 2017Many state-of-the-art ...
Offering diversity in the output of a recommender system is an active research question. Most of the...
Recommender systems for news articles on social media select and filter content through automatic pe...
Research on recommender systems has traditionally focused on the development of algorithms to improv...