Publications associées à Ontology filtering

From scattered sources to comprehensive technology landscape : A recommendation-based retrieval approach

Mapping the technology landscape is crucial for market actors to take informed investment decisions. However, given the large amount of data on the Web and its subsequent information overload, manually retrieving information is a seemingly ineffective and ...

ELSEVIER2023

The Case for Performance Interfaces for Hardware Accelerators

George Candea, Aikaterini Argyraki, Rishabh Ramesh Iyer, Jiacheng Ma

While systems designers are increasingly turning to hardware accelerators for performance gains, realizing these gains is painstaking and error-prone. It can take several person-months to determine if a given accelerator is a good fit for a given piece of ...

2023

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

Overcoming decision paralysis—A digital twin for decision making in energy system design

François Maréchal, Tuong-Van Nguyen, Julia Granacher

The design of efficient energy systems, through the development of new technologies and the improvement of current ones, requires the use of rigorous process synthesis methods for generating and analysing design alternatives. We introduce a digital twin of ...

2022

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

Positive and Negative Critiquing for VAE-based Recommenders

Boi Faltings, Diego Matteo Antognini

Providing explanations for recommended items allows users to refine the recommendations by critiquing parts of the explanations. As a result of revisiting critiquing from the perspective of multimodal generative models, recent work has proposed M&Ms-VAE, w ...

2022

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

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

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

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

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

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

Multi-armed Bandits in Action

Farnood Salehi

Making decisions is part and parcel of being human. Among a set of actions, we want to choose the one that has the highest reward. But the uncertainty of the outcome prevents us from always making the right decision. Making decisions under uncertainty can ...

EPFL2020

Measurement-system design for structural identification

Numa Joy Bertola

In developed countries, the management of existing civil infrastructure is challenging due to evolving functional requirements, aging and climate change. Due to conservative approaches in construction design and practice, infrastructure often has hidden re ...

EPFL2020

Auditing Radicalization Pathways on YouTube

Robert West, Manoel Horta Ribeiro

Non-profits, as well as the media, have hypothesized the existence of a radicalization pipeline on YouTube, claiming that users systematically progress towards more extreme content on the platform. Yet, there is to date no substantial quantitative evidence ...

ASSOC COMPUTING MACHINERY2020

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

Interdependent and Multi-Subject Privacy: Threats, Analysis and Protection

Alexandra-Mihaela Olteanu

In Alan Westin's generally accepted definition of privacy, he describes it as an individual's right 'to control, edit, manage, and delete information about them[selves] and decide when, how, and to what extent information is communicated to others.' There ...

EPFL2019

Unified and Scalable Incremental Recommenders with Consumed Item Packs

Rachid Guerraoui, Rhicheek Patra

Recommenders personalize the web content using collaborative filtering to relate users (or items). This work proposes to unify user-based, item-based and neural word embeddings types of recommenders under a single abstraction for their input, we name Consu ...

Springer2019

A Framework for Adaptive User Interface Generation based on User Behavioural Patterns

Kalpani Anuradha Welivita

The concept of adaptivity is crucial in enterprise software systems with a large user base. Adaptive user interfaces (AUI) is an emerging research area that enables customized user experience based on user activities. Most of the existing studies that are ...

IEEE2019

The (Co)-Location Sharing Game

Jean-Pierre Hubaux, Mathias Jacques Jean-Marc Humbert, Kévin Clément Huguenin, Alexandra-Mihaela Olteanu

Most popular location-based social networks, such as Facebook and Foursquare, let their (mobile) users post location and co-location (involving other users) information. Such posts bring social benefits to the users who post them but also to their friends ...

2019