Domenico Potena
About
In The Last Decade
Domenico Potena
72 papers receiving 597 citations
Peers
Comparison fields: 5 of 92
- Artificial Intelligence 291
- Information Systems 217
- Management Information Systems 176
- Computer Networks and Communications 127
- Management Science and Operations Research 75
Countries citing papers authored by Domenico Potena
This map shows the geographic impact of Domenico Potena'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 Domenico Potena with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Domenico Potena more than expected).
Fields of papers citing papers by Domenico Potena
This network shows the impact of papers produced by Domenico Potena. 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 Domenico Potena. The network helps show where Domenico Potena may publish in the future.
Co-authorship network of co-authors of Domenico Potena
This figure shows the co-authorship network connecting the top 25 collaborators of Domenico Potena. A scholar is included among the top collaborators of Domenico Potena 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 Domenico Potena. Domenico Potena is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 2 | |
| 3 | 1 | |
| 4 | 1 | |
| 5 | Emotion and sentiment analysis of tweets using BERT. | 34 |
| 6 | 16 | |
| 7 | How to Cope with Personnel Unavailability? Process Mining May Help! | 1 |
| 8 | Multi-Dimensional Contexts for Querying IoT Networks. | 2 |
| 9 | 2 | |
| 10 | An Approach to Extracting Thematic Views from Highly Heterogeneous Sources of a Data Lake. | 5 |
| 11 | APD tool:Mining anomalous patterns from event logs | 1 |
| 12 | 26 | |
| 13 | Towards process instances building for spaghetti processes | 2 |
| 14 | A semi-automatic methodology for the design of performance monitoring systems. | 4 |
| 15 | 2 | |
| 16 | Clustering of Process Schemas by Graph Mining Techniques (Extended Abstract). | 4 |
| 17 | 4 | |
| 18 | Hierarchical Clustering of Process Schemas. | 3 |
| 19 | KDDBroker: Description and Discovery of KDD Services. | 1 |
| 20 | Collaborative Knowledge Discovery in Databases: A Knowledge Exchange Perspective. | 6 |
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.