Massimo Ruffolo

466 citations
24 papers · 192 · h-index 8

Impact in

Papers in

Massimo Ruffolo

23 papers receiving 173 citations

Peers

Massimo Ruffolo
Comparison fields: 5 of 46
  • Information Systems 69
  • Artificial Intelligence 92
  • Computer Vision and Pattern Recognition 57
  • Medical Laboratory Technology 3
  • Management Science and Operations Research 20
Replace Philipp Heim with:
Philipp Heim Germany
Sagnik Ray Choudhury United States
Andreas Lommatzsch Germany
Svetlana Mansmann Germany
Arun Iyer India
Yutaka Kidawara Japan
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Salim Jouili Belgium
Mitchell Joblin Germany
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Citations per year

Countries citing papers authored by Massimo Ruffolo

Since Specialization
Citations

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

Fields of papers citing papers by Massimo Ruffolo

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Massimo Ruffolo, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Massimo Ruffolo Line = papers co-authored together Massimo Ruffolo links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 24 papers — load more, or switch the sort, to bring in the rest.

#Work
1 200956
2 201721
3 200216
4 200814
5 201012
6
Towards An Adaptive Mail Classifier
200211
7
Exploiting ASP for Semantic Information Extraction.
200510
8 20069
9 20116
10 20086
11 20074
12 20044
13
Enhancing Disjunctive Logic Programming for Ontology Specification.
20033
14 20123
15 20093
16
A Logic-Based Approach to Semantic Information Extraction
20062
17 20232
18 20212
19 20082
20 20182

About Massimo Ruffolo

Massimo Ruffolo is a scholar working on Artificial Intelligence, Information Systems, Computer Networks and Communications, Molecular Biology and Health Information Management, having authored 24 papers that have together received 192 indexed citations. Recurring topics across this work include Semantic Web and Ontologies (11 papers), Web Data Mining and Analysis (6 papers), Advanced Database Systems and Queries (4 papers), Logic, Reasoning, and Knowledge (3 papers), Biomedical Text Mining and Ontologies (3 papers), Electronic Health Records Systems (2 papers), Handwritten Text Recognition Techniques (2 papers) and Service-Oriented Architecture and Web Services (2 papers). The work is most often cited by research in Information Systems (69 citations), Artificial Intelligence (92 citations), Computer Vision and Pattern Recognition (57 citations), Medical Laboratory Technology (3 citations) and Management Science and Operations Research (20 citations). Massimo Ruffolo has collaborated with scholars based in Italy, United States and Germany. Frequent co-authors include Ermelinda Oro, Clara Pizzuti, Marco Manna, Domenico Saccà, Steffen Staab, Andrea Tagarelli, Giuseppe Manco, Elio Masciari, Michele Grimaldi and Pasquale Rullo. Their work appears in journals such as IEEE Transactions on Multimedia, Proceedings of the VLDB Endowment, Journal of Information Technology Case and Application Research, Acta Horticulturae and International Journal of Artificial Intelligence Tools.

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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