Diego Ceccarelli

586 citations
17 papers · 209 · h-index 8

Impact in

Papers in

    • Topic Modeling 9
    • Natural Language Processing Techniques 5
    • Advanced Graph Neural Networks 4
    • Semantic Web and Ontologies 3
    • Advanced Text Analysis Techniques 2
    • Recommender Systems and Techniques 3
    • Web Data Mining and Analysis 3

Diego Ceccarelli

15 papers receiving 191 citations

Peers

Diego Ceccarelli
Comparison fields: 5 of 30
  • Artificial Intelligence 169
  • Management Science and Operations Research 47
  • Information Systems 69
  • Communication 13
  • Signal Processing 18
Replace Günter Ladwig with:
Günter Ladwig Germany
Gerald Haesendonck Belgium
Osma Suominen Finland
Tanguy Urvoy France
Md. Hanif Seddiqui Bangladesh
Manuela Speranza Italy
Paramita Mirza Germany
Eric Crestan United States
Erdal Kuzey Germany
Xinying Song China
Diego Ceccarelli relative to Günter Ladwig Germany Günter Ladwig's profile →
Citations per field
00.5×9.7×
Günter Ladwig · 1×
Citations per year

Countries citing papers authored by Diego Ceccarelli

Since Specialization
Citations

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

Fields of papers citing papers by Diego Ceccarelli

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Diego Ceccarelli, 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 Diego Ceccarelli Line = papers co-authored together Diego Ceccarelli links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 201346
2 201242
3 201338
4 201717
5 201116
6 201215
7 20168
8
Dexter 2.0: an open source tool for semantically enriching data
20147
9 20176
10 20214
11 20163
12 20142
13 20132
14
Discovering Europeana users’ search behavior
20111
15 20131
16 20161
17 20140

About Diego Ceccarelli

Diego Ceccarelli is a scholar working on Artificial Intelligence, Information Systems, Computer Vision and Pattern Recognition, Computer Networks and Communications and Sociology and Political Science, having authored 17 papers that have together received 209 indexed citations. Recurring topics across this work include Topic Modeling (9 papers), Natural Language Processing Techniques (5 papers), Advanced Graph Neural Networks (4 papers), Semantic Web and Ontologies (3 papers), Recommender Systems and Techniques (3 papers), Web Data Mining and Analysis (3 papers), Complex Network Analysis Techniques (2 papers) and Advanced Text Analysis Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (169 citations), Management Science and Operations Research (47 citations), Information Systems (69 citations), Communication (13 citations) and Signal Processing (18 citations). Diego Ceccarelli has collaborated with scholars based in Italy, Spain and United Kingdom. Frequent co-authors include Raffaele Perego, Claudio Lucchese, Salvatore Orlando, Giovanni Tummarello, Renaud Delbru, Fabrizio Silvestri, Miles Osborne, Roi Blanco, Leif Azzopardi and Juan M. Fernández‐Luna. Their work appears in journals such as ACM SIGIR Forum, Computational Intelligence, ERCIM news/ERCIM news online edition, ISTI Open Portal and CINECA IRIS Institutial research information system (University of Pisa).

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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