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The role of recommendation systems in the diversity of content consumption on platforms is a much-debated issue. The quantitative state of the art often overlooks the existence of individual attitudes toward guidance, and eventually of…
Slanted news coverage strongly affects public opinion. This is especially true for coverage on politics and related issues, where studies have shown that bias in the news may influence elections and other collective decisions. Due to its…
The Personalization of information has taken recommender systems at a very high level. With personalization these systems can generate user specific recommendations accurately and efficiently. User profiling helps personalization, where…
Wikidata is one of the most important sources of structured data on the web, built by a worldwide community of volunteers. As a secondary source, its contents must be backed by credible references; this is particularly important as Wikidata…
Personalized news recommendation is an important technique to help users find their interested news information and alleviate their information overload. It has been extensively studied over decades and has achieved notable success in…
Personalized text-to-image generation aims to create images tailored to user-defined concepts and textual descriptions. Balancing the fidelity of the learned concept with its ability for generation in various contexts presents a significant…
The growing popularity of short-form video content, such as YouTube Shorts, has transformed user engagement on digital platforms, raising critical questions about the role of recommendation algorithms in shaping user experiences. These…
Human activities can be seen as sequences of events, which are crucial to understanding societies. Disproportional event distribution for different demographic groups can manifest and amplify social stereotypes, and potentially jeopardize…
Although the content in scientific publications is increasingly challenging, it is necessary to investigate another important problem, that of scientific information understanding. For this proposed problem, we investigate novel methods to…
Citation recommendation describes the task of recommending citations for a given text. Due to the overload of published scientific works in recent years on the one hand, and the need to cite the most appropriate publications when writing…
Social media platforms today strive to improve user experience through AI recommendations, yet the value of such recommendations vanishes as users do not understand the reasons behind them. This issue arises because explainability in social…
Wikipedia has been turned into an immensely popular crowd-sourced encyclopedia for information dissemination on numerous versatile topics in the form of subscription free content. It allows anyone to contribute so that the articles remain…
Recommendation to groups of users is a challenging and currently only passingly studied task. Especially the evaluation aspect often appears ad-hoc and instead of truly evaluating on groups of users, synthesizes groups by merging individual…
The increasing reliance on complex algorithmic systems by online platforms has sparked a growing need for algorithm auditing, a methodology evaluating these systems' functionality and impact. In this paper, we systematically review 176…
There is much debate on how public participation and expertise can be brought together in collaborative knowledge environments. One of the experiments addressing the issue directly is Citizendium. In seeking to harvest the strengths (and…
Opinion summarisation aims to summarise the salient information and opinions presented in documents such as product reviews, discussion forums, and social media texts into short summaries that enable users to effectively understand the…
Access to textual and visual information for visually impaired persons becomes very difficult with screen readers which are not adapted to different websites.This paper analyses the use of different technologies for access digital content…
Most text-to-image customization techniques fine-tune models on a small set of \emph{personal concept} images captured in minimal contexts. This often results in the model becoming overfitted to these training images and unable to…
Producing a reduced version of a source text, as in generic or focused summarization, inherently involves two distinct subtasks: deciding on targeted content and generating a coherent text conveying it. While some popular approaches address…
We propose a new similarity measure between texts which, contrary to the current state-of-the-art approaches, takes a global view of the texts to be compared. We have implemented a tool to compute our textual distance and conducted…