Cataldo Musto

3.1k total citations
100 papers, 1.4k citations indexed

About

Cataldo Musto is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Cataldo Musto has authored 100 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 78 papers in Information Systems, 75 papers in Artificial Intelligence and 16 papers in Computer Vision and Pattern Recognition. Recurrent topics in Cataldo Musto's work include Recommender Systems and Techniques (76 papers), Topic Modeling (37 papers) and Advanced Graph Neural Networks (24 papers). Cataldo Musto is often cited by papers focused on Recommender Systems and Techniques (76 papers), Topic Modeling (37 papers) and Advanced Graph Neural Networks (24 papers). Cataldo Musto collaborates with scholars based in Italy, Netherlands and Denmark. Cataldo Musto's co-authors include Giovanni Semeraro, Pasquale Lops, Marco de Gemmis, Fedelucio Narducci, Marco Polignano, Pierpaolo Basile, Marijn Koolen, Dietmar Jannach, Toine Bogers and Alain D. Starke and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Information Sciences.

In The Last Decade

Cataldo Musto

87 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Cataldo Musto Italy 23 919 916 235 140 104 100 1.4k
Joeran Beel Germany 20 854 0.9× 960 1.0× 144 0.6× 133 0.9× 142 1.4× 65 1.6k
Yunbo Cao China 24 1.6k 1.7× 989 1.1× 241 1.0× 157 1.1× 111 1.1× 79 2.0k
Mária Bieliková Slovakia 19 790 0.9× 865 0.9× 200 0.9× 176 1.3× 61 0.6× 186 1.6k
Longqi Yang United States 15 549 0.6× 634 0.7× 237 1.0× 210 1.5× 206 2.0× 45 1.4k
Xavier Ochôa Ecuador 21 503 0.5× 680 0.7× 215 0.9× 89 0.6× 79 0.8× 114 1.8k
Marco de Gemmis Italy 27 1.2k 1.3× 1.3k 1.4× 394 1.7× 208 1.5× 166 1.6× 135 2.0k
Nava Tintarev United Kingdom 17 688 0.7× 697 0.8× 242 1.0× 167 1.2× 172 1.7× 49 1.3k
Toine Bogers Denmark 15 446 0.5× 671 0.7× 135 0.6× 128 0.9× 87 0.8× 91 1.0k
Pasquale Lops Italy 25 1.1k 1.2× 1.4k 1.5× 416 1.8× 192 1.4× 180 1.7× 141 2.0k
Stefano Mizzaro Italy 20 767 0.8× 946 1.0× 184 0.8× 188 1.3× 187 1.8× 102 1.6k

Countries citing papers authored by Cataldo Musto

Since Specialization
Citations

This map shows the geographic impact of Cataldo Musto's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Cataldo Musto with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Cataldo Musto more than expected).

Fields of papers citing papers by Cataldo Musto

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Cataldo Musto. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Cataldo Musto. The network helps show where Cataldo Musto may publish in the future.

Co-authorship network of co-authors of Cataldo Musto

This figure shows the co-authorship network connecting the top 25 collaborators of Cataldo Musto. A scholar is included among the top collaborators of Cataldo Musto based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Cataldo Musto. Cataldo Musto is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Musto, Cataldo, et al.. (2025). DistillRecDial: A Knowledge-Distilled Dataset Capturing User Diversity in Conversational Recommendation. CINECA IRIS Institutial research information system (University of Pisa). 726–735.
2.
Musto, Cataldo, et al.. (2024). Towards Green Recommender Systems: Investigating the Impact of Data Reduction on Carbon Footprint and Algorithm Performances. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 866–871. 4 indexed citations
3.
Musto, Cataldo, et al.. (2024). Instructing and Prompting Large Language Models for Explainable Cross-domain Recommendations. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 298–308. 10 indexed citations
4.
Lops, Pasquale, et al.. (2024). Reproducibility of LLM-based Recommender Systems: the Case Study of P5 Paradigm. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 116–125. 1 indexed citations
5.
Musto, Cataldo, et al.. (2024). Recommending Healthy and Sustainable Meals exploiting Food Retrieval and Large Language Models. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 1057–1061.
6.
Musto, Cataldo, et al.. (2024). Recommender systems based on neuro-symbolic knowledge graph embeddings encoding first-order logic rules. User Modeling and User-Adapted Interaction. 34(5). 2039–2083. 4 indexed citations
7.
Anelli, Vito Walter, et al.. (2024). Sixth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS). 1245–1249.
8.
Musto, Cataldo, et al.. (2024). Improving Transformer-based Sequential Conversational Recommendations through Knowledge Graph Embeddings. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 172–182. 3 indexed citations
9.
Lops, Pasquale, Cataldo Musto, & Marco Polignano. (2023). Accountable Knowledge-aware Recommender Systems. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 306–308. 1 indexed citations
10.
Musto, Cataldo, et al.. (2023). Towards Sustainability-aware Recommender Systems: Analyzing the Trade-off Between Algorithms Performance and Carbon Footprint. Archivio istituzionale della ricerca (Alma Mater Studiorum Università di Bologna). 856–862. 16 indexed citations
11.
Lops, Pasquale, et al.. (2023). Reproducibility Analysis of Recommender Systems relying on Visual Features: traps, pitfalls, and countermeasures. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 554–564. 1 indexed citations
12.
Musto, Cataldo, Marco de Gemmis, Pasquale Lops, & Giovanni Semeraro. (2020). Generating post hoc review-based natural language justifications for recommender systems. User Modeling and User-Adapted Interaction. 31(3). 629–673. 32 indexed citations
13.
Lai, Mirko, Valerio Basile, Fabio Poletto, et al.. (2020). “Contro L’Odio”: A Platform for Detecting, Monitoring and Visualizing Hate Speech against Immigrants in Italian Social Media. SHILAP Revista de lepidopterología. 6(1). 77–97. 7 indexed citations
14.
Polignano, Marco, et al.. (2020). HealthAssistantBot: A Personal Health Assistant for the Italian Language. IEEE Access. 8. 107479–107497. 40 indexed citations
15.
Cena, Federica, Amon Rapp, Cataldo Musto, & Giovanni Semeraro. (2020). Generating Recommendations From Multiple Data Sources: A Methodological Framework for System Design and Its Application. IEEE Access. 8. 183430–183447. 8 indexed citations
16.
Bogers, Toine, Pasquale Lops, Marijn Koolen, Cataldo Musto, & Giovanni Semeraro. (2015). CBRecSys 2016. New Trends on Content-Based Recommender Systems: Proceedings of the 3rd Workshop on New Trends on Content-Based Recommender Systems co-located with 10th ACM Conference on Recommender Systems (RecSys 2016). Conference on Recommender Systems.
17.
Musto, Cataldo, et al.. (2014). Financial Product Recommendation through Case-based Reasoning and Diversification Techniques.. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 4 indexed citations
18.
Musto, Cataldo, Pierpaolo Basile, Pasquale Lops, Marco de Gemmis, & Giovanni Semeraro. (2014). Linked Open Data-enabled Strategies for Top-N Recommendations.. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 49–56. 12 indexed citations
19.
Musto, Cataldo, Fedelucio Narducci, Marco de Gemmis, Pasquale Lops, & Giovanni Semeraro. (2010). An IR-Based Approach for Tag Recommendation.. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 65–69. 2 indexed citations
20.
Musto, Cataldo, Fedelucio Narducci, Marco de Gemmis, Pasquale Lops, & Giovanni Semeraro. (2009). STaR: a social tag recommender system. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 215–227. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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