
This volume contains the Proceedings of the Short Papers of the 20th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems, IPMU 2024, held July 22-26, 2024, at the Centro de Congressos do Instituto Superior Técnico in Lisbon, Portugal. The conference was organized by INESC-ID and IDMEC of Instituto Superior Técnico, Universidade de Lisboa. The IPMU conference is organized every two years. It aims to bring together scientists working on methods for the management of uncertainty and aggregation of information in intelligent systems. Since 1986, the IPMU conference has provided a forum for exchanging ideas between theoreticians and practitioners working in these areas and related fields. For IPMU2024, the authors had the option of submitting either regular papers or shortpapers. The present volume contains 45 of the accepted short papers. Each of these papers was examined by the program chairs and selected reviewers for relevance and technical contribution, and contains a summary of a work that was presented and discussed orally during one of the IPMU2024 sessions.
Information aggregation, Uncertainty management, Intelligent Systems
Information aggregation, Uncertainty management, Intelligent Systems
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
