In working environments where prolonged sitting is ubiquitous, maintaining correct posture is crucial to alleviating musculoskeletal problems and improving general well-being. This research presents an innovative approach for assessing sitting postures ...

Adaptive and personalized systems have become pervasive technologies, gradually playing an increasingly important role in our daily lives. Indeed, we are now accustomed to interacting with algorithms that leverage the power of Language Models (LLMs) to ...

Conversational Recommender Systems (CRS) have recently drawn attention due to their capacity of delivering personalized recommendations through multi-turn natural language interactions. In this paper, we fit into this research line and we introduce a ...

In this paper, we introduce a Knowledge-aware Recommender System (KARS) based on Graph Neural Networks that exploit pre-trained content-based embeddings to improve the representation of users and items. Our approach relies on the intuition that textual ...

The 10th edition of the Joint Workshop on Interfaces and Human Decision Making for Recommender Systems was held as part of the 17th ACM Conference on Recommender Systems (RecSys), the premier international forum for the presentation of new research ...

Preference elicitation is a crucial step for every recommendation algorithm. In this paper, we present a strategy that allows users to express their preferences and needs through natural language statements. In particular, our natural language ...$\mathrm{}$

Users of online recipe websites tend to prefer unhealthy foods. Their popularity undermines the healthiness of traditional food recommender systems, as many users lack nutritional knowledge to make informed food decisions. Moreover, the presented ...$\mathrm{}$$\mathrm{}$

Knowledge-aware recommender systems represent one of the most innovative research directions in the area of recommender systems, aiming at giving meaning to information expressed in natural language and obtaining a deeper comprehension of the ...

Reproducibility is an important requirement for scientific progress, and the lack of reproducibility for a large amount of published research can hinder the progress over the state-of-the-art. This concerns several research areas, and recommender ...

In this paper, we present a comparative analysis of the trade-off between the performance of state-of-the-art recommendation algorithms and their environmental impact. In particular, we compared 18 popular recommendation algorithms in terms of both ...

Recommender systems (RSs) have undoubtedly played a significant role in addressing the information overload problem by efficiently filtering and suggesting relevant items to users. These systems use both explicit and implicit user preferences to filter ...

In this paper, we present a strategy to provide users with knowledge-aware recommendations based on the combination of graph neural networks and sentence encoders. In particular, our approach relies on the intuition that different data sources (i.e., ...

Adaptive and personalized systems have become pervasive technologies, gradually playing an increasingly important role in our daily lives. Indeed, we are now used to interacting with algorithms that help us in several scenarios, ranging from services ...

The Italian Public Administration (PA) relies on costly manual analyses to ensure the GDPR compliance of public documents and secure personal data. Despite recent advances in Artificial Intelligence (AI) have benefited many legal fields, the ...

Virtual Customer Assistants (VCAs) are revolutionizing the way users interact with machines. VCAs allow a far more natural interaction, and are gaining an increasingly large role in customer service. The financial domain is especially ...

Digital Assistants are overgrowing in the mobile application industry and are now implemented in various commercial devices. So far, their use in the health domain is limited and often narrowed to remote monitoring of specific patient ...

• Definition of a lifelong health user model.
• Definition of an intelligent ...

In this paper, we present a knowledge-aware recommendation framework based on neuro-symbolic graph embeddings that encode first-order logical (FOL) rules. In particular, our workflow starts from a knowledge graph (KG) encoding user preferences (based on ...

The FinRec workshop series offers a central forum for the study and discussion of the domain-specific aspects, challenges, and opportunities of RecSys and other related technologies in the financial services domain. Six years after the second edition of ...

The constant increase in the amount of data and information available on the Web has made the development of systems that can support users in making relevant decisions increasingly important. Recommender systems (RSs) have emerged as tools to address ...

The phenomenon of hate messages on the web is unfortunately in continuous expansion and evolution. Even if the big companies that offer their users a social network service have expressly included in their terms of services rules against hate messages, ...