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- 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-articleDecember 2023
Tell me what you Like: introducing natural language preference elicitation strategies in a virtual assistant for the movie domain
- 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 ...
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- 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-articleMarch 2023
An AI framework to support decisions on GDPR compliance
Journal of Intelligent Information Systems (JIIS), Volume 61, Issue 2Oct 2023, Pages 541–568https://doi.org/10.1007/s10844-023-00782-4AbstractThe 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 ...
- review-articleFebruary 2023
Virtual Customer Assistants in finance: From state of the art and practices to design guidelines
Computer Science Review (COMPSR), Volume 47, Issue CFeb 2023https://doi.org/10.1016/j.cosrev.2023.100534AbstractVirtual 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 ...
- 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 ...
- research-articleJuly 2022
Lexicon Enriched Hybrid Hate Speech Detection with Human-Centered Explanations
UMAP '22 Adjunct: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and PersonalizationJuly 2022, Pages 184–191https://doi.org/10.1145/3511047.3537688The 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, ...
- extended-abstractJuly 2022
A Virtual Assistant for the Movie Domain Exploiting Natural Language Preference Elicitation Strategies
- Alessandro Francesco Maria Martina,
- Cataldo Musto,
- Andrea Iovine,
- Marco de Gemmis,
- Fedelucio Narducci,
- Giovanni Semeraro
UMAP '22 Adjunct: Adjunct Proceedings of the 30th ACM Conference on User Modeling, Adaptation and PersonalizationJuly 2022, Pages 7–12https://doi.org/10.1145/3511047.3536407In this paper, we present a strategy to introduce natural language preference elicitation in a virtual assistant for the movie domain. Our approach allows users to express preferences on objective movie features (e.g., actors, directors, etc.) that are ...
- 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 ...
- 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 ...
- research-articleJuly 2021
Generating post hoc review-based natural language justifications for recommender systems
User Modeling and User-Adapted Interaction (KLU-USER), Volume 31, Issue 3Jul 2021, Pages 629–673https://doi.org/10.1007/s11257-020-09270-8AbstractIn this article, we present a framework to build post hoc natural language justifications that supports the suggestions generated by a recommendation algorithm. Our methodology is based on the intuition that reviews’ excerpts contain much relevant ...
- research-articleApril 2021
Improving preference elicitation in a conversational recommender system with active learning strategies
SAC '21: Proceedings of the 36th Annual ACM Symposium on Applied ComputingMarch 2021, Pages 1375–1382https://doi.org/10.1145/3412841.3442013Conversational Recommender Systems are gaining more and more attention in the last years. They are characterized by the ability of establishing a multi-turn dialog with the user. Since those systems generally work in a cold-start situation, most of the ...
- extended-abstractSeptember 2020
Interfaces and Human Decision Making for Recommender Systems
- Peter Brusilovsky,
- Marco de Gemmis,
- Alexander Felfernig,
- Pasquale Lops,
- John O'Donovan,
- Giovanni Semeraro,
- Martijn C. Willemsen
RecSys '20: Proceedings of the 14th ACM Conference on Recommender SystemsSeptember 2020, Pages 613–618https://doi.org/10.1145/3383313.3411539As an interactive intelligent system, recommender systems are developed to give recommendations that match users’ preferences. Since the emergence of recommender systems, a large majority of research focuses on objective accuracy criteria and less ...