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- research-articleJune 2024
Human Pose Estimation for Explainable Corrective Feedbacks in Office Spaces
UMAP Adjunct '24: Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and PersonalizationJune 2024, Pages 264–275https://doi.org/10.1145/3631700.3665184In 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 ...
- research-articleJune 2024
Improving Transformer-based Sequential Conversational Recommendations through Knowledge Graph Embeddings
- Alessandro Petruzzelli,
- Alessandro Francesco Maria Martina,
- Giuseppe Spillo,
- Cataldo Musto,
- Marco De Gemmis,
- Pasquale Lops,
- Giovanni Semeraro
UMAP '24: Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and PersonalizationJune 2024, Pages 172–182https://doi.org/10.1145/3627043.3659565Conversational 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 ...
- short-paperJune 2024
Evaluating Content-based Pre-Training Strategies for a Knowledge-aware Recommender System based on Graph Neural Networks
UMAP '24: Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and PersonalizationJune 2024, Pages 165–171https://doi.org/10.1145/3627043.3659548In 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 ...
- research-articleJanuary 2024
Report on the 10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2023) at ACM RecSys 2023
- Peter Brusilovsky,
- Marco de Gemmis,
- Alexander Felfernig,
- Pasquale Lops,
- Marco Polignano,
- Giovanni Semeraro,
- Martijn C. Willemsen
ACM SIGIR Forum (SIGIR), Volume 57, Issue 2December 2023, Article No.: 17, Pages 1–6https://doi.org/10.1145/3642979.3642999The 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 ...
- research-articleOctober 2023
AI-based decision support system for public procurement
AbstractTenders are powerful means of investment of public funds and represent a strategic development resource. Thus, improving the efficiency of procuring entities and developing evaluation models turn out to be essential to facilitate e-procurement ...
Highlights- A Decision Support System integrating structured/unstructured data about tenders.
- Semantic search engine for tenders documentation to allow information retrieval.
- Search engine based on OIE (Open Information Extraction) techniques.
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- research-articleOctober 2023
ClayRS: An end-to-end framework for reproducible knowledge-aware recommender systems
AbstractKnowledge-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 ...
- research-articleSeptember 2023
- research-articleSeptember 2023
Reproducibility Analysis of Recommender Systems relying on Visual Features: traps, pitfalls, and countermeasures
RecSys '23: Proceedings of the 17th ACM Conference on Recommender SystemsSeptember 2023, Pages 554–564https://doi.org/10.1145/3604915.3609492Reproducibility 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 ...
- extended-abstractSeptember 2023
10th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’23)
- Peter Brusilovsky,
- Marco De Gemmis,
- Alexander Felfernig,
- Pasquale Lops,
- Marco Polignano,
- Giovanni Semeraro,
- Martijn C. Willemsen
RecSys '23: Proceedings of the 17th ACM Conference on Recommender SystemsSeptember 2023, Pages 1255–1258https://doi.org/10.1145/3604915.3608758Recommender 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 ...
- extended-abstractJune 2023
Accountable Knowledge-aware Recommender Systems
UMAP '23: Proceedings of the 31st ACM Conference on User Modeling, Adaptation and PersonalizationJune 2023, Pages 306–308https://doi.org/10.1145/3565472.3595605Knowledge-aware algorithms represent one of the most innovative research directions in the area of recommender systems. The use of different types of content representation requires new methods to extract descriptive features to adopt in the ...
- research-articleJune 2023Best Student Paper
Combining Graph Neural Networks and Sentence Encoders for Knowledge-aware Recommendations
UMAP '23: Proceedings of the 31st ACM Conference on User Modeling, Adaptation and PersonalizationJune 2023, Pages 1–12https://doi.org/10.1145/3565472.3592965In 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., ...
- research-articleJanuary 2023
HELENA: An intelligent digital assistant based on a Lifelong Health User Model
Information Processing and Management: an International Journal (IPRM), Volume 60, Issue 1Jan 2023https://doi.org/10.1016/j.ipm.2022.103124AbstractDigital 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 ...
Highlights- Definition of a lifelong health user model.
- Definition of an intelligent ...
- short-paperSeptember 2022
Knowledge-aware Recommendations Based on Neuro-Symbolic Graph Embeddings and First-Order Logical Rules
RecSys '22: Proceedings of the 16th ACM Conference on Recommender SystemsSeptember 2022, Pages 616–621https://doi.org/10.1145/3523227.3551484In 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 ...
- introductionSeptember 2022
Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’22)
- Peter Brusilovsky,
- Marco de Gemmis,
- Alexander Felfernig,
- Pasquale Lops,
- Marco Polignano,
- Giovanni Semeraro,
- Martijn C. Willemsen
RecSys '22: Proceedings of the 16th ACM Conference on Recommender SystemsSeptember 2022, Pages 667–670https://doi.org/10.1145/3523227.3547413The 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 ...
- extended-abstractJuly 2022
Semantics-aware Content Representations for Reproducible Recommender Systems (SCoRe)
UMAP '22: Proceedings of the 30th ACM Conference on User Modeling, Adaptation and PersonalizationJuly 2022, Pages 354–356https://doi.org/10.1145/3503252.3533723In the traditional categorization of recommendation techniques, content-based methods are often considered as an alternative to the most widely adopted collaborative filtering approaches. Content-based recommender systems suggest items similar to a user ...
- research-articleApril 2022
An empirical evaluation of active learning strategies for profile elicitation in a conversational recommender system
Journal of Intelligent Information Systems (JIIS), Volume 58, Issue 2Apr 2022, Pages 337–362https://doi.org/10.1007/s10844-021-00683-4AbstractConversational Recommender Systems have received widespread attention in both research and practice. They assist people in finding relevant and interesting items through a multi-turn conversation. The use of natural language interaction also ...
- extended-abstractMarch 2022
First Workshop on Adaptive and Personalized Explainable User Interfaces (APEx-UI 2022)
IUI '22 Companion: Companion Proceedings of the 27th International Conference on Intelligent User InterfacesMarch 2022, Pages 1–3https://doi.org/10.1145/3490100.3511168Adaptation and personalization are crucial aspects of the design and development of successful Artificial Intelligence systems, from search engines and recommender systems to wearable devices. The increased desire for customization inevitably leads to ...
- research-articleSeptember 2021
Together is Better: Hybrid Recommendations Combining Graph Embeddings and Contextualized Word Representations
RecSys '21: Proceedings of the 15th ACM Conference on Recommender SystemsSeptember 2021, Pages 187–198https://doi.org/10.1145/3460231.3474272In this paper, we present a hybrid recommendation framework based on the combination of graph embeddings and contextual word representations. Our approach is based on the intuition that each of the above mentioned representation models heterogeneous (...
- extended-abstractSeptember 2021
Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS’21)
- Peter Brusilovsky,
- Marco de Gemmis,
- Alexander Felfernig,
- Elisabeth Lex,
- Pasquale Lops,
- Giovanni Semeraro,
- Martijn C. Willemsen
RecSys '21: Proceedings of the 15th ACM Conference on Recommender SystemsSeptember 2021, Pages 783–786https://doi.org/10.1145/3460231.3470927Recommender systems were originally developed as interactive intelligent systems that can proactively guide users to items that match their preferences. Despite its origin on the crossroads of HCI and AI, the majority of research on recommender systems ...
- research-articleAugust 2021
MyrrorBot: A Digital Assistant Based on Holistic User Models for Personalized Access to Online Services
ACM Transactions on Information Systems (TOIS), Volume 39, Issue 4Article No.: 46, Pages 1–34https://doi.org/10.1145/3447679In this article, we present MyrrorBot, a personal digital assistant implementing a natural language interface that allows the users to: (i) access online services, such as music, video, news, andfood recommendations, in a personalized way, by exploiting a ...