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Paolo Tomeo
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2010 – 2019
- 2019
- [j5]Ignacio Fernández-Tobías, Iván Cantador, Paolo Tomeo, Vito Walter Anelli
, Tommaso Di Noia:
Addressing the user cold start with cross-domain collaborative filtering: exploiting item metadata in matrix factorization. User Model. User Adapt. Interact. 29(2): 443-486 (2019) - 2018
- [c14]Alejandro Bellogín
Neighbor Selection for Cold Users in Collaborative Filtering with Positive-Only Feedback. CAEPIA 2018: 3-12 - [r1]Tommaso Di Noia, Paolo Tomeo:
Recommender Systems Based on Linked Open Data. Encyclopedia of Social Network Analysis and Mining. 2nd Ed. 2018 - 2017
- [j4]Paolo Tomeo, Ignacio Fernández-Tobías, Iván Cantador, Tommaso Di Noia:
Addressing the Cold Start with Positive-Only Feedback Through Semantic-Based Recommendations. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 25(Supplement-2): 57-78 (2017) - [j3]Tommaso Di Noia
Adaptive multi-attribute diversity for recommender systems. Inf. Sci. 382-383: 234-253 (2017) - [c13]Corrado Magarelli, Azzurra Ragone, Paolo Tomeo, Tommaso Di Noia, Matteo Palmonari, Andrea Maurino, Eugenio Di Sciascio:
Schema-aware Feature Selection in Linked Data-based Recommender Systems. IIR 2017: 67-71 - [c12]Vito Walter Anelli, Vito Bellini, Tommaso Di Noia, Wanda La Bruna, Paolo Tomeo, Eugenio Di Sciascio:
On the Role of Time and Sessions in Diversifying Recommendation Results. IIR 2017: 92-96 - [c11]Azzurra Ragone
Schema-summarization in linked-data-based feature selection for recommender systems. SAC 2017: 330-335 - [c10]Vito Walter Anelli
An Analysis on Time- and Session-aware Diversification in Recommender Systems. UMAP 2017: 270-274 - 2016
- [j2]Tommaso Di Noia
Building a relatedness graph from Linked Open Data: A case study in the IT domain. Expert Syst. Appl. 44: 354-366 (2016) - [j1]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) - [c9]Paolo Tomeo, Ignacio Fernández-Tobías, Tommaso Di Noia, Iván Cantador:
Exploiting Linked Open Data in Cold-start Recommendations with Positive-only Feedback. CERI 2016: 11 - [c8]Jindrich Mynarz, Marek Dudás, Paolo Tomeo, Vojtech Svátek:
Generating examples of paths summarizing RDF datasets. SEMANTiCS (Posters, Demos, SuCCESS) 2016 - [c7]Aleksandra Karpus
Rating Prediction with Contextual Conditional Preferences. KDIR 2016: 419-424 - [c6]Ignacio Fernández-Tobías, Paolo Tomeo, Iván Cantador, Tommaso Di Noia, Eugenio Di Sciascio:
Accuracy and Diversity in Cross-domain Recommendations for Cold-start Users with Positive-only Feedback. RecSys 2016: 119-122 - 2015
- [c5]Tommaso Di Noia, Vito Claudio Ostuni, Jessica Rosati, Paolo Tomeo, Eugenio Di Sciascio:
Adaptive Diversity in Recommender Systems. IIR 2015 - [c4]Paolo Tomeo, Tommaso Di Noia, Marco de Gemmis, Pasquale Lops, Giovanni Semeraro, Eugenio Di Sciascio:
Exploiting Regression Trees as User Models for Intent-Aware Multi-attribute Diversity. CBRecSys@RecSys 2015: 2-9 - [c3]Phuong T. Nguyen
Content-Based Recommendations via DBpedia and Freebase: A Case Study in the Music Domain. ISWC (1) 2015: 605-621 - [c2]Phuong T. Nguyen
An evaluation of SimRank and Personalized PageRank to build a recommender system for the Web of Data. WWW (Companion Volume) 2015: 1477-1482 - 2014
- [c1]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
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