Fabio Mercorio

1.7k total citations
65 papers, 926 citations indexed

About

Fabio Mercorio is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, Fabio Mercorio has authored 65 papers receiving a total of 926 indexed citations (citations by other indexed papers that have themselves been cited), including 52 papers in Artificial Intelligence, 19 papers in Information Systems and 10 papers in Computer Vision and Pattern Recognition. Recurrent topics in Fabio Mercorio's work include Topic Modeling (17 papers), Natural Language Processing Techniques (9 papers) and Data Quality and Management (9 papers). Fabio Mercorio is often cited by papers focused on Topic Modeling (17 papers), Natural Language Processing Techniques (9 papers) and Data Quality and Management (9 papers). Fabio Mercorio collaborates with scholars based in Italy, United Kingdom and United States. Fabio Mercorio's co-authors include Mario Mezzanzanica, Mirko Cesarini, Lorenzo Malandri, Roberto Boselli, Daniele Magazzeni, Giuseppe Della Penna, Emilio Colombo, Benedetto Intrigila, Antonio Picariello and Vincenzo Moscato and has published in prestigious journals such as Applied Soft Computing, Decision Support Systems and Knowledge-Based Systems.

In The Last Decade

Fabio Mercorio

60 papers receiving 871 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Fabio Mercorio Italy 17 461 221 105 90 66 65 926
Juan Miguel Gómez-Berbís Spain 17 379 0.8× 387 1.8× 146 1.4× 53 0.6× 37 0.6× 51 948
Xin Fu China 19 186 0.4× 155 0.7× 110 1.0× 83 0.9× 76 1.2× 58 982
Seng‐Cho T. Chou Taiwan 16 257 0.6× 198 0.9× 193 1.8× 75 0.8× 53 0.8× 59 934
David Martens Belgium 13 466 1.0× 295 1.3× 100 1.0× 49 0.5× 44 0.7× 78 1.1k
Fernando Martínez‐Plumed Spain 13 331 0.7× 104 0.5× 60 0.6× 53 0.6× 33 0.5× 35 807
Xiaomei Bai China 17 383 0.8× 374 1.7× 39 0.4× 76 0.8× 47 0.7× 48 1.0k
Anas Ratib Alsoud Jordan 16 218 0.5× 134 0.6× 53 0.5× 39 0.4× 34 0.5× 55 855
Olawande Daramola Nigeria 14 231 0.5× 231 1.0× 45 0.4× 29 0.3× 50 0.8× 70 714
Shaha Al‐Otaibi Saudi Arabia 15 282 0.6× 238 1.1× 61 0.6× 68 0.8× 24 0.4× 58 908
Sarabjot Singh Anand United Kingdom 15 353 0.8× 550 2.5× 82 0.8× 129 1.4× 65 1.0× 54 1.0k

Countries citing papers authored by Fabio Mercorio

Since Specialization
Citations

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

Fields of papers citing papers by Fabio Mercorio

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Fabio Mercorio

This figure shows the co-authorship network connecting the top 25 collaborators of Fabio Mercorio. A scholar is included among the top collaborators of Fabio Mercorio 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 Fabio Mercorio. Fabio Mercorio 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.
Malandri, Lorenzo, et al.. (2024). SeNSe: embedding alignment via semantic anchors selection. International Journal of Data Science and Analytics. 20(1). 167–181. 2 indexed citations
2.
Malandri, Lorenzo, et al.. (2024). Alignment of Multilingual Embeddings to Estimate Job Similarities in Online Labour Market. BOA (University of Milano-Bicocca). 1–10. 1 indexed citations
3.
Cambria, Erik, et al.. (2022). A survey on XAI and natural language explanations. Information Processing & Management. 60(1). 103111–103111. 64 indexed citations
4.
Malandri, Lorenzo, et al.. (2022). ConvXAI: a System for Multimodal Interaction with Any Black-box Explainer. Cognitive Computation. 15(2). 613–644. 14 indexed citations
5.
Malandri, Lorenzo, et al.. (2022). Embeddings Evaluation Using a Novel Measure of Semantic Similarity. Cognitive Computation. 14(2). 749–763. 9 indexed citations
6.
Gozzi, Noemi, Lorenzo Malandri, Fabio Mercorio, & Alessandra Pedrocchi. (2022). XAI for myo-controlled prosthesis: Explaining EMG data for hand gesture classification. Knowledge-Based Systems. 240. 108053–108053. 41 indexed citations
7.
Malandri, Lorenzo, et al.. (2022). A Survey on XAI for Cyber Physical Systems in Medicine. BOA (University of Milano-Bicocca). 265–270. 3 indexed citations
8.
Malandri, Lorenzo, et al.. (2022). FFTree: A flexible tree to handle multiple fairness criteria. Information Processing & Management. 59(6). 103099–103099. 9 indexed citations
9.
Malandri, Lorenzo, et al.. (2021). ContrXT: Generating contrastive explanations from any text classifier. Information Fusion. 81. 103–115. 10 indexed citations
10.
Malandri, Lorenzo, et al.. (2020). Skills2Job: A recommender system that encodes job offer embeddings on graph databases. Applied Soft Computing. 101. 107049–107049. 40 indexed citations
11.
Amato, Flora, Aniello Castiglione, Fabio Mercorio, et al.. (2018). Multimedia story creation on social networks. Future Generation Computer Systems. 86. 412–420. 25 indexed citations
12.
Boselli, Roberto, Mirko Cesarini, Stefania Marrara, et al.. (2017). WoLMIS: a labor market intelligence system for classifying web job vacancies. Journal of Intelligent Information Systems. 51(3). 477–502. 54 indexed citations
13.
Boselli, Roberto, Mirko Cesarini, Fabio Mercorio, & Mario Mezzanzanica. (2017). Labour market intelligence for supporting decision making. BOA (University of Milano-Bicocca). 74–81.
14.
Fox, Maria, et al.. (2016). Heuristic planning for PDDL+ domains. BOA (University of Milano-Bicocca). 3213–3219. 20 indexed citations
15.
Penna, Giuseppe Della, Benedetto Intrigila, Daniele Magazzeni, & Fabio Mercorio. (2015). UPMurphi Released: PDDL+ Planning for Hybrid Systems. BOA (University of Milano-Bicocca). 36–40. 1 indexed citations
16.
Amato, Flora, Roberto Boselli, Mirko Cesarini, et al.. (2015). Challenge: Processing web texts for classifying job offers. View. 460–463. 26 indexed citations
17.
Mezzanzanica, Mario, Roberto Boselli, Mirko Cesarini, & Fabio Mercorio. (2014). Improving Data Cleansing Accuracy - A Model-based Approach. BOA (University of Milano-Bicocca). 189–201. 1 indexed citations
18.
Boselli, Roberto, Mirko Cesarini, Fabio Mercorio, & Mario Mezzanzanica. (2013). Semantic Annotation of unstructured Wiki Knowledge according to Ontological Models. BOA (University of Milano-Bicocca). 75–80. 1 indexed citations
19.
Mezzanzanica, Mario, Mirko Cesarini, Fabio Mercorio, & Roberto Boselli. (2012). Towards the use of Model Checking for performing Data Consistency Evaluation and Cleansing. BOA (University of Milano-Bicocca). 163–177. 2 indexed citations
20.
Penna, Giuseppe Della, Benedetto Intrigila, Daniele Magazzeni, Fabio Mercorio, & Enrico Tronci. (2011). Proceedings of the 8th International Conference on Informatics in Control, Automation and Robotics (ICINCO-11). 15 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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