In information retrieval, relevance is perceived as a multidimensional and dynamic concept
influenced by user, task, and domain factors. Relying on this perspective, researchers have …

With the growth of electronic data and the expansion of the World Wide Web (WWW), many
classic existing retrieval models and systems ignore information about the actual user and …

A new model for aggregating multiple criteria evaluations for relevance assessment is
proposed. An Information Retrieval context is considered, where relevance is modeled as a …

Abstract Information Retrieval is a complex task, which deals with both the subjectivity
related to the user's needs and the uncertainty and vagueness that characterize the retrieval …

This paper shortly discusses the main issues related to the problem of personalizing search.
To overcome the “one size fits all” behavior of most search engines and Information …

The relevance of geographic information has become an emerging problem in geographic
information science due to an enormous increase in volumes of data at high spatial …

Creating systems that can interpret and manage the ambiguity and subjectivity of the
representation and retrieval of information is one of the issues facing information systems …

In this paper, we propose a novel approach to consider multiple dimensions of relevance in
cross-encoder re-ranking. On the one hand, cross-encoders constitute an effective solution …

This paper focuses on modelling information usefulness. More precisely, it aims at
characterizing how useful a piece of information is for a cognitive agent which has some …

It has been shown that relevance judgment of documents is influenced by multiple factors
beyond topicality. Some multidimensional user relevance models (MURM) proposed in …