Publications related to Diversifying Group Recommendation

Secure Interface Design Leveraging Hardware/Software Support

Computer systems rely heavily on abstraction to manage the exponential growth of complexity across hardware and software. Due to practical considerations of compatibility between components of these complex systems across generations, developers have favou ...

EPFL2024

Device and system as human interactive surface

Jamie Paik, Fabio Zuliani

A force-feedback surface that creates and modulates distinctive profile and stiffnessto interact with a user in contact thereto, the surface being functionally independentto be used as a single module but can be customized to extend the application indiver ...

2023

Adapting Haptic Feedback for Guided Meditation

Nicolas Henchoz, Cédric Duchene, Andreas Sonderegger, Romain Simon Collaud, Emily Clare Groves, Yoann Pierre Douillet

Technology supporting meditation is a multimillion-dollar market that continues to grow. There is also strong academic interest to understand and improve the impact technology can have for the user experience of practitioners. However, little work investig ...

2023

Assessing the implementation of user-centred design standards on assistive technology for persons with visual impairments: a systematic review

Klaus Benedikt Schönenberger, Mario Andres Chavarria Varon

Despite scientific and technological advances in the field of assistive technology (AT) for people with visual impairment (VI), technological designs are frequently based on a poor understanding of the physical and social context of use, resulting in devic ...

Frontiers Media Sa2023

Dynamic Personalized Ranking

Jérémie Rappaz

Personalized ranking methods are at the core of many systems that learn to produce recommendations from user feedbacks. Their primary objective is to identify relevant items from very large vocabularies and to assist users in discovering new content. These ...

EPFL2022

TEE-based decentralized recommender systems: The raw data sharing redemption

Anne-Marie Kermarrec, Akash Balasaheb Dhasade, Nevena Dresevic, Rafael Pereira Pires

Recommenders are central in many applications today. The most effective recommendation schemes, such as those based on collaborative filtering (CF), exploit similarities between user profiles to make recommendations, but potentially expose private data. Fe ...

2022

Interacting with Explanations through Critiquing

Boi Faltings, Claudiu-Cristian Musat, Diego Matteo Antognini

Using personalized explanations to support recommendations has been shown to increase trust and perceived quality. However, to actually obtain better recommendations, there needs to be a means for users to modify the recommendation criteria by interacting ...

2021

p Recommender systems: Past, present, future

Pearl Pu Faltings

The origins of modern recommender systems date back to the early 1990s when they were mainly applied experimentally to personal email and information filtering. Today, 30 years later, personalized recommendations are ubiquitous and research in this highly ...

AMER ASSOC ARTIFICIAL INTELL2021

The Theory, Practice, and Ethical Challenges of Designing a Diversity-Aware Platform for Social Relations

Daniel Gatica-Perez, Lakmal Buddika Meegahapola

Diversity-aware platform design is a paradigm that responds to the ethical challenges of existing social media platforms. Available platforms have been criticized for minimizing users' autonomy, marginalizing minorities, and exploiting users' data for prof ...

ASSOC COMPUTING MACHINERY2021

Immunizing Systems from Distant Failures by Limiting Lamport Exposure

Bryan Alexander Ford, Cristina Basescu

Failures far away from a user should intuitively be less likely to affect that user. Today's ecosystem miserably fails this test, however, despite high-availability best practices. Correlated and cascading failures – triggered by misconfigurations, bugs, a ...

Association for Computing Machinery2021

Multi-Step Critiquing User Interface for Recommender Systems

Boi Faltings, Diego Matteo Antognini, Diana Andreea Petrescu

Recommendations with personalized explanations have been shown to increase user trust and perceived quality and help users make better decisions. Moreover, such explanations allow users to provide feedback by critiquing them. Several algorithms for recomme ...

ASSOC COMPUTING MACHINERY2021

User Expectations of Conversational Chatbots Based on Online Reviews

Pearl Pu Faltings, Ekaterina Svikhnushina, Alexandru Placinta

Open-domain chatbots that can engage in a conversation on any topic received significant attention in the last several years, which opened opportunities for studying user interaction with them. Drawing from reviews of chatbots posted on Google Play, we exp ...

ASSOC COMPUTING MACHINERY2021

Conversational Multi-Hop Reasoning with Neural Commonsense Knowledge and Symbolic Logic Rules

Forough Arabshahi, Antoine Bosselut

One of the challenges faced by conversational agents is their inability to identify unstated presumptions of their users' commands, a task trivial for humans due to their common sense. In this paper, we propose a zeroshot commonsense reasoning system for c ...

ASSOC COMPUTATIONAL LINGUISTICS-ACL2021

Method of analysing handwritten items

Pierre Dillenbourg, Thibault Lucien Christian Asselborn, Wafa Monia Benkaouar Johal

The present invention according to one embodiment concerns a computer-implemented method of analysing handwritten characters produced by a user. The method comprises: collecting (107) handwritten characters of the user, the user being part of a given user ...

2021

Interplay between upsampling and regularization for provider fairness in recommender systems

Mirko Marras

Considering the impact of recommendations on item providers is one of the duties of multi-sided recommender systems. Item providers are key stakeholders in online platforms, and their earnings and plans are influenced by the exposure their items receive in ...

SPRINGER2021

Advances in Bias-aware Recommendation on the Web

Mirko Marras

The goal of this tutorial is to provide the WSDM community with recent advances on the assessment and mitigation of data and algorithmic bias in recommender systems. We first introduce conceptual foundations, by presenting the state of the art and describi ...

ASSOC COMPUTING MACHINERY2021

Design Approaches for Creating Person-Centered, Context Sensitive, and Sustainable Assistive Technology with the Global South

Klaus Benedikt Schönenberger, Mario Andres Chavarria Varon

The implementation of non-user-centered design is sometimes effective for traditionally mass-produced items; however, these methods do not take into account local needs, resources, and cultures, and the history of individual people and communities in low- ...

Oxford University Press2021

Does spontaneous motion lead to intuitive Body-Machine Interfaces? A fitness study of different body segments for wearable telerobotics

Dario Floreano, Matteo Macchini, Fabrizio Schiano

Human-Robot Interfaces (HRIs) represent a crucial component in telerobotic systems. Body-Machine Interfaces (BoMIs) based on body motion can feel more intuitive than standard HRIs for naive users as they leverage humans’ natural control capability over the ...

2021

Chirok: a post-refinement tool to analyse absolute structure

Philip Pattison

Chirok is software for a post-refinement test of the absolute structure. The software allows a user to calculate a distribution of the measure of chirality based on intensity quotients and linked to the Flack parameter. The distribution is fitted by a set ...

2020

Caching (Bivariate) Gaussians

Michael Christoph Gastpar, Guillaume Jean Op 't Veld

Caching is a technique that alleviates networks during peak hours by transmitting partial information before a request for any is made. In a lossy setting of Gaussian databases, we study a single-user model in which good caching strategies minimize the dat ...

2020