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2020 – today
- 2026
[i4]Aditya Sinha, Harald Steck, Vito Ostuni, Matteo Rinaldi:
Beyond Continuity: Challenges of Context Switching in Multi-Turn Dialogue with LLMs. CoRR abs/2605.09268 (2026)- 2025
- [c19]Yunan Hu
, Mark Thornburg, Mario García-Armas, Vito Ostuni, Anne Cocos, Kriti Kohli, Christoph Kofler, Rob Saltiel:
Cold Starting a New Content Type: A Case Study with Netflix Live. RecSys 2025: 927-930 - [e1]Mária Bieliková, Pavel Kordík, Markus Schedl, Marco de Gemmis, Sole Pera, Rodrigo Alves, Olivier Jeunen, Vito Ostuni:
Proceedings of the Nineteenth ACM Conference on Recommender Systems, RecSys 2025, Prague, Czech Republic, September 22-26, 2025. ACM 2025, ISBN 979-8-4007-1364-4 [contents] - [i3]Yaochen Zhu, Harald Steck, Dawen Liang, Yinhan He, Vito Ostuni, Jundong Li, Nathan Kallus:
Rank-GRPO: Training LLM-based Conversational Recommender Systems with Reinforcement Learning. CoRR abs/2510.20150 (2025) - 2024
- [c18]Moumita Bhattacharya, Vito Ostuni, Sudarshan Lamkhede:
Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn). RecSys 2024: 793-795 - [i2]Moumita Bhattacharya, Vito Ostuni, Sudarshan Lamkhede:
Joint Modeling of Search and Recommendations Via an Unified Contextual Recommender (UniCoRn). CoRR abs/2408.10394 (2024) - 2023
- [c17]Vito Ostuni, Christoph Kofler, Manjesh Nilange, Sudarshan Lamkhede, Dan Zylberglejd:
Search Personalization at Netflix. WWW (Companion Volume) 2023: 756-758 - 2020
- [i1]Mucun Tian, Chun Guo, Vito Ostuni, Zhen Zhu:
Counterfactual Learning to Rank using Heterogeneous Treatment Effect Estimation. CoRR abs/2007.09798 (2020)
2010 – 2019
- 2019
- [c16]Vito Claudio Ostuni:
"Just play something awesome": the personalization powering voice interactions at Pandora. RecSys 2019: 523 - 2017
- [j4]Sergio Oramas, Vito Claudio Ostuni, Tommaso Di Noia, Xavier Serra, Eugenio Di Sciascio:
Sound and Music Recommendation with Knowledge Graphs. ACM Trans. Intell. Syst. Technol. 8(2): 21:1-21:21 (2017) - [c15]Tao Ye, Denis Parra, Vito Ostuni, Tao Wang:
LSRS'17: Workshop on Large-Scale Recommender Systems. RecSys 2017: 390-391 - 2016
- [j3]Tommaso Di Noia, Vito Claudio Ostuni, Jessica Rosati, Paolo Tomeo, Eugenio Di Sciascio, Roberto Mirizzi, Claudio Bartolini:
Building a relatedness graph from Linked Open Data: A case study in the IT domain. Expert Syst. Appl. 44: 354-366 (2016) - [j2]Tommaso Di Noia, Vito Claudio Ostuni, Paolo Tomeo, Eugenio Di Sciascio:
SPrank: Semantic Path-Based Ranking for Top-N Recommendations Using Linked Open Data. ACM Trans. Intell. Syst. Technol. 8(1): 9:1-9:34 (2016) - 2015
- [c14]Tommaso Di Noia, Vito Claudio Ostuni, Jessica Rosati, Paolo Tomeo, Eugenio Di Sciascio:
Adaptive Diversity in Recommender Systems. IIR 2015 - [c13]Tommaso Di Noia, Vito Claudio Ostuni:
Recommender Systems and Linked Open Data. Reasoning Web 2015: 88-113 - [c12]Vito Claudio Ostuni, Tommaso Di Noia, Eugenio Di Sciascio, Sergio Oramas, Xavier Serra:
A Semantic Hybrid Approach for Sound Recommendation. WWW (Companion Volume) 2015: 85-86 - 2014
- [c11]Andrea Calì, Roberto De Virgilio, Tommaso Di Noia, Luca Menichetti, Roberto Mirizzi, Luca Nardini, Vito Claudio Ostuni, Fabrizio Rebecca, Marco Ungania:
Semantic Search in RealFoodTrade. AMW 2014 - [c10]Vito Claudio Ostuni, Tommaso Di Noia, Roberto Mirizzi, Eugenio Di Sciascio:
A Linked Data Recommender System Using a Neighborhood-Based Graph Kernel. EC-Web 2014: 89-100 - [c9]Tommaso Di Noia, Iván Cantador, Vito Claudio Ostuni:
Linked Open Data-Enabled Recommender Systems: ESWC 2014 Challenge on Book Recommendation. SemWebEval@ESWC 2014: 129-143 - [c8]Vito Claudio Ostuni, Tommaso Di Noia, Roberto Mirizzi, Eugenio Di Sciascio:
Top-N Recommendations from Implicit Feedback Leveraging Linked Open Data. IIR 2014: 20-27 - [c7]Tommaso Di Noia, Vito Claudio Ostuni, Jessica Rosati, Paolo Tomeo, Eugenio Di Sciascio:
An analysis of users' propensity toward diversity in recommendations. RecSys 2014: 285-288 - 2013
- [j1]Tommaso Di Noia, Vito Claudio Ostuni, Francesco Pesce, Giulio Binetti, David Naso, Francesco Paolo Schena, Eugenio Di Sciascio:
An end stage kidney disease predictor based on an artificial neural networks ensemble. Expert Syst. Appl. 40(11): 4438-4445 (2013) - [c6]Vito Claudio Ostuni, Giosia Gentile, Tommaso Di Noia, Roberto Mirizzi, Davide Romito, Eugenio Di Sciascio:
Mobile Movie Recommendations with Linked Data. CD-ARES 2013: 400-415 - [c5]Vito Claudio Ostuni, Tommaso Di Noia, Eugenio Di Sciascio, Roberto Mirizzi:
Top-N recommendations from implicit feedback leveraging linked open data. RecSys 2013: 85-92 - 2012
- [c4]Tommaso Di Noia, Roberto Mirizzi, Vito Claudio Ostuni, Davide Romito, Markus Zanker:
Linked open data to support content-based recommender systems. I-SEMANTICS 2012: 1-8 - [c3]Roberto Mirizzi, Tommaso Di Noia, Azzurra Ragone, Vito Claudio Ostuni, Eugenio Di Sciascio:
Movie Recommendation with DBpedia. IIR 2012: 101-112 - [c2]Tommaso Di Noia, Roberto Mirizzi, Vito Claudio Ostuni, Davide Romito:
Exploiting the web of data in model-based recommender systems. RecSys 2012: 253-256 - [c1]Vito Claudio Ostuni, Tommaso Di Noia, Roberto Mirizzi, Davide Romito, Eugenio Di Sciascio:
Cinemappy: a Context-aware Mobile App for Movie Recommendations boosted by DBpedia. SeRSy 2012: 37-48
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last updated on 2026-06-09 22:57 CEST by the dblp team
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