Fedelucio Narducci

1.8k total citations
75 papers, 727 citations indexed

About

Fedelucio Narducci is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Fedelucio Narducci has authored 75 papers receiving a total of 727 indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Artificial Intelligence, 47 papers in Information Systems and 14 papers in Computer Vision and Pattern Recognition. Recurrent topics in Fedelucio Narducci's work include Recommender Systems and Techniques (41 papers), Topic Modeling (24 papers) and Semantic Web and Ontologies (10 papers). Fedelucio Narducci is often cited by papers focused on Recommender Systems and Techniques (41 papers), Topic Modeling (24 papers) and Semantic Web and Ontologies (10 papers). Fedelucio Narducci collaborates with scholars based in Italy, United States and Denmark. Fedelucio Narducci's co-authors include Giovanni Semeraro, Marco de Gemmis, Pasquale Lops, Cataldo Musto, Marco Polignano, Pierpaolo Basile, Tommaso Di Noia, Vito Walter Anelli, Eugenio Di Sciascio and Yashar Deldjoo and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.

In The Last Decade

Fedelucio Narducci

67 papers receiving 702 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fedelucio Narducci Italy 15 463 388 124 64 43 75 727
Angelika Maag Australia 7 476 1.0× 213 0.5× 57 0.5× 96 1.5× 22 0.5× 22 795
Svetlin Bostandjiev United States 8 279 0.6× 384 1.0× 278 2.2× 73 1.1× 31 0.7× 9 643
Maryam Heidari United States 16 395 0.9× 217 0.6× 59 0.5× 124 1.9× 32 0.7× 24 646
Anastasios Tombros United Kingdom 13 463 1.0× 490 1.3× 95 0.8× 64 1.0× 49 1.1× 42 876
Maria Soledad Pera United States 15 423 0.9× 454 1.2× 59 0.5× 118 1.8× 13 0.3× 117 805
Pierpaolo Basile Italy 15 776 1.7× 455 1.2× 130 1.0× 85 1.3× 13 0.3× 89 1.0k
Carina Silberer Germany 11 1.1k 2.4× 180 0.5× 243 2.0× 65 1.0× 35 0.8× 19 1.4k
Max Goldman United States 11 282 0.6× 274 0.7× 87 0.7× 48 0.8× 23 0.5× 19 776
Chris Newell Switzerland 4 199 0.4× 351 0.9× 120 1.0× 143 2.2× 24 0.6× 4 580
Nazlia Omar Malaysia 19 982 2.1× 392 1.0× 53 0.4× 75 1.2× 14 0.3× 134 1.3k

Countries citing papers authored by Fedelucio Narducci

Since Specialization
Citations

This map shows the geographic impact of Fedelucio Narducci'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 Fedelucio Narducci with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Fedelucio Narducci more than expected).

Fields of papers citing papers by Fedelucio Narducci

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Fedelucio Narducci. 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 Fedelucio Narducci. The network helps show where Fedelucio Narducci may publish in the future.

Co-authorship network of co-authors of Fedelucio Narducci

This figure shows the co-authorship network connecting the top 25 collaborators of Fedelucio Narducci. A scholar is included among the top collaborators of Fedelucio Narducci 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 Fedelucio Narducci. Fedelucio Narducci 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.
Sorino, Paolo, Caterina Bonfiglio, Rossella Donghia, et al.. (2025). MORIX: Machine learning-aided framework for lethality detection and MORtality inference with eXplainable artificial intelligence in MAFLD subjects. SHILAP Revista de lepidopterología. 7. 100176–100176.
2.
Sorino, Paolo, et al.. (2025). Neural Musical Instruments through Brain-Computer Interface and Biofeedback. IRIS Research product catalog (Sapienza University of Rome). 489–494.
3.
Lombardi, Angela, et al.. (2025). Machine learning classification of motivational states: Insights from EEG analysis of perception and imagery. Expert Systems with Applications. 275. 127076–127076. 2 indexed citations
4.
Sorino, Paolo, et al.. (2025). Detecting label noise in longitudinal Alzheimer’s data with explainable artificial intelligence. Brain Informatics. 12(1). 15–15. 1 indexed citations
5.
6.
Deldjoo, Yashar, et al.. (2024). Interactive Question Answering Systems: Literature Review. ACM Computing Surveys. 56(9). 1–38. 13 indexed citations
7.
Sorino, Paolo, et al.. (2024). EmoSynth Real Time Emotion-Driven Sound Texture Synthesis via Brain-Computer Interface. IRIS Research product catalog (Sapienza University of Rome). 616–621. 1 indexed citations
8.
Noia, Tommaso Di, et al.. (2024). Wearable Devices and Brain-Computer Interfaces for User Modelling (WeBIUM). IRIS Research product catalog (Sapienza University of Rome). 597–600.
9.
Anelli, Vito Walter, et al.. (2024). Sixth Knowledge-aware and Conversational Recommender Systems Workshop (KaRS). 1245–1249.
10.
Lombardi, Angela, Paolo Sorino, Elvira Brattico, et al.. (2024). NeuroSense: A Novel EEG Dataset Utilizing Low-Cost, Sparse Electrode Devices for Emotion Exploration. IEEE Access. 12. 159296–159315. 2 indexed citations
11.
Sorino, Paolo, et al.. (2024). ARIEL: Brain-Computer Interfaces meet Large Language Models for Emotional Support Conversation. IRIS Research product catalog (Sapienza University of Rome). 601–609. 1 indexed citations
12.
Narducci, Fedelucio, et al.. (2024). AgoneTest: Automated creation and assessment of Unit tests leveraging Large Language Models. CINECA IRIS Institutional Research Information System (University of Bari Aldo Moro). 2440–2441. 1 indexed citations
13.
Narducci, Fedelucio, et al.. (2023). Virtual Customer Assistants in finance: From state of the art and practices to design guidelines. Computer Science Review. 47. 100534–100534. 9 indexed citations
14.
Bortone, Ilaria, Francesco Bottiglione, Tommaso Di Noia, et al.. (2022). Combining Biomechanical Features and Machine Learning Approaches to Identify Fencers’ Levels for Training Support. Applied Sciences. 12(23). 12350–12350. 8 indexed citations
15.
Narducci, Fedelucio, et al.. (2021). A General Aspect-Term-Extraction Model for Multi-Criteria Recommendations (Long paper).. Conference on Recommender Systems. 1 indexed citations
16.
Polignano, Marco, et al.. (2020). HealthAssistantBot: A Personal Health Assistant for the Italian Language. IEEE Access. 8. 107479–107497. 40 indexed citations
17.
Narducci, Fedelucio, et al.. (2018). A Framework for Building Chat-based Recommender Systems.. 2482. 1 indexed citations
18.
Narducci, Fedelucio, Matteo Palmonari, & Giovanni Semeraro. (2013). Cross-language Semantic Matching for Discovering Links to e-gov Services in the LOD Cloud. BOA (University of Milano-Bicocca). 992. 21–32. 7 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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