Tutorial Day: July 8, 2018
Type: half-day
Presenters:
Abstract: Recommender systems for groups are becoming increasingly important since many information needs originate from group and social activities, such as listening to mu- sic, watching movies, traveling, and many more. There has been substantial progress on systems which recommend items to groups of users. However, many challenges remain. The goal of this tutorial is to introduce group recommendations and group modeling to the UMAP audience. First we will introduce the problem of making recommendations to groups and adapting to groups, and give an overview of the state-of-the art approaches to group recommendations. Moreover, we will also analyze more challenging topics, such as, including different behavioural aspects into group modeling, and evaluation of group recom- mendations. Throughout, hands-on activities will be included. The tutorial will conclude with a summary of challenges and open issues.
Type: half-day
Presenters:
Abstract: Most works in the field of recommender systems are focused on the matrix completion problem, where for each user-item-pair only one interaction (e.g., a rating) is considered. In many application domains, however, multiple user-item interactions of different types can be recorded over time, and this information can be used to build richer individual user models and to discover additional behavioral patterns that can be leveraged in the recommendation process.
In this tutorial, we review existing works that consider infor- mation from such sequentially-ordered user-item interaction logs in the recommendation process. Based on this review, we describe a categorization of the corresponding recommendation tasks and goals, summarize existing algorithmic solutions, discuss method- ological approaches when benchmarking what we call sequence-aware recommender systems, and outline open challenges in the area.
The tutorial will based on a recent survey paper published by the presenters.
Slides: link to slideshare
Type: half-day
Presenters:
Abstract: We live in an age in which the dependency on technological tools is inescapable. At the same time, privacy-related issues are emerging in a way that we are at the breakpoint of losing control over our data. Information sharing by social-network users can result in violations of privacy and security. For example, when a user is asking for a personalised service, he may find his revealed contact details may become the subject of harassment (cyber-bullying) or become a potential victim of online deception or identity theft. Moreover, as Tim Berners-Lee stated, “The major players are making profit from our data. Therefore we lose out on the benefits we could realise if we had direct control over this data and chose when and with whom to share it”. Today, more than ever, users need to keep control over their personal data when they ask for a personalised service. In this tutorial, I propose to address how to reach the delicate balance between privacy and personalization.