In this paper, I present a novel approach for implementing a stream-based Recommender System (RecSys). I propose to add RecSys operators to an application-independent Data Stream ...
We describe a novel approach that integrates user-generated tags with standard Matrix Factorization to allow users to interactively control recommendations. The tag information is...
We introduce HRS, a recommender that exploits user reviews and identifies the features that are most likely appealing to users. HRS incorporates this knowledge into the recommenda...
Recommender systems have been around for decades to help people find the best matching item in a pre-defined item set. Knowledge-based recommender systems are used to match user...
Victor de Graaff, Anne van de Venis, Maurice van K...
We present our solution to the 2015 RecSys Challenge [1]. This challenge was based on a large scale dataset of over 9.2 million user-item click sessions from an online e-commerce ...
Food recommenders have been touted as a useful tool to help people achieve a healthy diet. Here we incorporate nutrition into the recommender problem by examining the feasibility ...
Even though there exist multiple approaches to build recommendation algorithms, algebraic techniques based on vector and matrix representations are predominant in the field. Notw...
The item cold-start problem is of a great importance in collaborative filtering (CF) recommendation systems. It arises when new items are added to the inventory and the system ca...
Michal Aharon, Oren Anava, Noa Avigdor-Elgrabli, D...
We propose to augment rating based recommender systems by providing the user with additional information which might help him in his choice or in the understanding of the recommen...