Paolo Viappiani
- Artificial Intelligence top 5%
- Information Systems top 5%
- Management Science and Operations Research top 5%
- Computer Networks and Communications top 10%
- Signal Processing top 5%
- Co-authors
- Pearl PuCraig BoutilierBoi FaltingsGabriella PigozziAlexis TsoukiàsPatrice PernyMarc TorrensKevin Regan
- Topics
- Data Management and Algorithms (11 papers)Constraint Satisfaction and Optimization (8 papers)Recommender Systems and Techniques (8 papers)
- Partner nations
- SwitzerlandCanadaFrance
In The Last Decade
Paolo Viappiani
31 papers receiving 419 citations
Peers
Comparison fields: 5 of 51
- Artificial Intelligence 212
- Information Systems 171
- Management Science and Operations Research 154
- Computer Networks and Communications 129
- Signal Processing 125
Countries citing papers authored by Paolo Viappiani
This map shows the geographic impact of Paolo Viappiani'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 Paolo Viappiani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Paolo Viappiani more than expected).
Fields of papers citing papers by Paolo Viappiani
This network shows the impact of papers produced by Paolo Viappiani. 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 Paolo Viappiani. The network helps show where Paolo Viappiani may publish in the future.
Co-authorship network of co-authors of Paolo Viappiani
This figure shows the co-authorship network connecting the top 25 collaborators of Paolo Viappiani. A scholar is included among the top collaborators of Paolo Viappiani 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 Paolo Viappiani. Paolo Viappiani 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 | 7 | |
| 3 | 7 | |
| 4 | 3 | |
| 5 | 32 | |
| 6 | 54 | |
| 7 | A Bayesian concept learning approach to crowdsourcing | 1 |
| 8 | Optimal Bayesian Recommendation Sets and Myopically Optimal Choice Query Sets | 46 |
| 9 | 6 | |
| 10 | Optimal set recommendations based on regret | 4 |
| 11 | 31 | |
| 12 | 0 | |
| 13 | 27 | |
| 14 | The lookahead principle for preference elicitation: Experimental results | 3 |
| 15 | Evaluating preference-based search tools: a tale of two approaches | 15 |
| 16 | 68 | |
| 17 | A Study of User's Online Decision Making Behavior | 2 |
| 18 | 3 | |
| 19 | Stimulating preference expression using suggestions | 7 |
| 20 | 8 |
About Paolo Viappiani
Paolo Viappiani is a scholar working on General Decision Sciences, Management Science and Operations Research and Signal Processing, having authored 33 papers that have together received 459 indexed citations. Recurring topics across this work include Data Management and Algorithms (11 papers), Constraint Satisfaction and Optimization (8 papers) and Recommender Systems and Techniques (8 papers). The work is most often cited by research in General Decision Sciences (31 citations), Management Science and Operations Research (154 citations) and Signal Processing (125 citations). Paolo Viappiani has collaborated with scholars based in Switzerland, Canada and France. Frequent co-authors include Pearl Pu, Craig Boutilier, Boi Faltings, Boi Faltings, Gabriella Pigozzi, Alexis Tsoukiàs, Patrice Perny, Marc Torrens, Kevin Regan and Bart Peintner. Their work appears in journals such as Journal of Nutrition, Artificial Intelligence and Lecture notes in computer science.
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.