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 …

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 …

With the wealth of information produced by social networks, smartphones, medical or
financial applications, speculations have been raised about the sensitivity of such data in …

While many multidimensional models of relevance have been posited, prior studies have
been largely exploratory rather than confirmatory. Lacking a methodological framework to …

Document retrieval is the task of returning relevant textual resources for a given user query.
In this paper, we investigate whether the semantic analysis of the query and the documents …

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 short paper presents initial results from a project, in which we investigated differences
in how users view relevant and irrelevant Web pages on their visits and revisits. The users' …

Document relevance has been the primary focus in the design, optimization and evaluation
of retrieval systems. Traditional testcollections are constructed by asking judges the …

There may be prioritizations among criteria in some practical multi-criteria decision making
(MCDM) problems, which are called prioritized MCDM ones. The investigation of such a kind …

In Machine Learning scenarios, privacy is a crucial concern when models have to be trained
with private data coming from users of a service, such as a recommender system, a location …