Leo Iaquinta
- Information Systems top 5%
- Artificial Intelligence
- Computer Vision and Pattern Recognition
- Management Science and Operations Research
- Sociology and Political Science
- Co-authors
- Giovanni SemeraroMarco de GemmisPasquale LopsPiero MolinoMichele FilanninoPierpaolo BasileFedelucio NarducciCataldo Musto
- Topics
- Recommender Systems and Techniques (9 papers)Image Retrieval and Classification Techniques (5 papers)Topic Modeling (3 papers)
- Journals
- Information SciencesNeuroepidemiologyInternational Journal of Information and Communication Technology
In The Last Decade
Leo Iaquinta
14 papers receiving 216 citations
Peers
Comparison fields: 5 of 53
- Information Systems 151
- Artificial Intelligence 89
- Computer Vision and Pattern Recognition 58
- Management Science and Operations Research 33
- Sociology and Political Science 24
Countries citing papers authored by Leo Iaquinta
This map shows the geographic impact of Leo Iaquinta'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 Leo Iaquinta with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Leo Iaquinta more than expected).
Fields of papers citing papers by Leo Iaquinta
This network shows the impact of papers produced by Leo Iaquinta. 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 Leo Iaquinta. The network helps show where Leo Iaquinta may publish in the future.
Co-authorship network of co-authors of Leo Iaquinta
This figure shows the co-authorship network connecting the top 25 collaborators of Leo Iaquinta. A scholar is included among the top collaborators of Leo Iaquinta 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 Leo Iaquinta. Leo Iaquinta is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 1 | |
| 2 | 3 | |
| 3 | 1 | |
| 4 | 46 | |
| 5 | A fuzzy model for service value assessment | 0 |
| 6 | SMART project: Industrial and Academic Collaboration for Service Design. | 0 |
| 7 | User segmentation in e-Government services | 1 |
| 8 | 7 | |
| 9 | Lightweight Approach to the Cold Start Problem in the Video Lecture Recommendation | 6 |
| 10 | 6 | |
| 11 | 4 | |
| 12 | 118 | |
| 13 | META - MultilanguagE Text Analyzer | 9 |
| 14 | The JUMP project: domain ontologies and linguistic knowledge @ work | 3 |
| 15 | 4 | |
| 16 | 3 | |
| 17 | 18 |
About Leo Iaquinta
Leo Iaquinta is a scholar working on Information Systems, Conservation and Computer Vision and Pattern Recognition, having authored 17 papers that have together received 230 indexed citations. Recurring topics across this work include Recommender Systems and Techniques (9 papers), Image Retrieval and Classification Techniques (5 papers) and Topic Modeling (3 papers). The work is most often cited by research in Information Systems (151 citations), Computer Vision and Pattern Recognition (58 citations) and Artificial Intelligence (89 citations). Leo Iaquinta has collaborated with scholars based in Italy and Spain. Frequent co-authors include Giovanni Semeraro, Marco de Gemmis, Pasquale Lops, Piero Molino, Michele Filannino, Pierpaolo Basile, Fedelucio Narducci, Cataldo Musto, Annalina Caputo and Anna Lisa Gentile. Their work appears in journals such as Information Sciences, Neuroepidemiology and International Journal of Information and Communication Technology.
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.