Publications associées à Why the World Reads Wikipedia: Beyond English Speakers

A Large-Scale Characterization of How Readers Browse Wikipedia

Robert West, Tiziano Piccardi, Akhil Arora

Despite the importance and pervasiveness of Wikipedia as one of the largest platforms for open knowledge, surprisingly little is known about how people navigate its content when seeking information. To bridge this gap, we present the first systematic large ...

ASSOC COMPUTING MACHINERY2023

A large scale study of reader interactions with images on Wikipedia

Tiziano Piccardi, Daniele Rama

Wikipedia is the largest source of free encyclopedic knowledge and one of the most visited sites on the Web. To increase reader understanding of the article, Wikipedia editors add images within the text of the article's body. However, despite their widespr ...

SPRINGER2022

How We Use Wikipedia: Studying Readers' Behavior with Navigation Traces

Tiziano Piccardi

In the information age, the Web and the growing global connectivity drastically simplified our access to information. Learning and fact-checking from online resources is nowadays part of our daily routine. Studying the dynamic associated with online conten ...

EPFL2022

Dynamic pattern recognition in large-scale graphs with applications to social networks

Volodymyr Miz

A graph is a versatile data structure facilitating representation of interactions among objects in various complex systems. Very often these objects have attributes whose measurements change over time, reflecting the dynamics of the system. This general da ...

EPFL2020

Building blocks for commodity augmented reality-based molecular visualization and modeling in web browsers

Luciano Andres Abriata

For years, immersive interfaces using virtual and augmented reality (AR) for molecular visualization and modeling have promised a revolution in the way how we teach, learn, communicate and work in chemistry, structural biology and related areas. However, m ...

2020

A Graph-structured Dataset for Wikipedia Research

Pierre Vandergheynst, Nicolas Aspert, Volodymyr Miz, Benjamin Ricaud

Wikipedia is a rich and invaluable source of information. Its central place on the Web makes it a particularly interesting object of study for scientists. Researchers from different domains used various complex datasets related to Wikipedia to study langua ...

ACM2019

Automated Taxonomy Induction and its Applications

Amit Gupta

Machine-readable semantic knowledge in the form of taxonomies (i.e., a collection of is-a edges) has proved to be beneficial in an array of NLP tasks including inference, textual entailment, question answering and information extraction. Such widespread ut ...

EPFL2017

Wikipedia Chemical Structure Explorer: substructure and similarity searching of molecules from Wikipedia

Luc Patiny, Michaël Giuseppe Zasso

Background: Wikipedia, the world's largest and most popular encyclopedia is an indispensable source of chemistry information. It contains among others also entries for over 15,000 chemicals including metabolites, drugs, agrochemicals and industrial chemica ...

Biomed Central Ltd2015

Towards a highly effective and robust Web credibility evaluation system

Karl Aberer, Xin Liu

By leveraging crowdsourcing, Web credibility evaluation systems (WCESs) have become a promising tool to assess the credibility of Web content, e.g., Web pages. However, existing systems adopt a passive Way to collect users' credibility ratings, which incur ...

Elsevier Science Bv2015

B-hist: Entity-centric search over personal web browsing history

Karl Aberer, Philippe Cudré-Mauroux, Michele Catasta, Jean-Eudes Marie Ranvier

Web Search is increasingly entity centric; as a large fraction of common queries target specific entities, search results get progressively augmented with semi-structured and multimedia information about those entities. However, search over personal web br ...

Elsevier2014