RT Conference Proceedings
T1 Dealing with Belief Uncertainty in Domain Models.
A1 Burgueño-Caballero, Lola
A1 Muñoz Ariza, Paula
A1 Clarisó, Robert
A1 Cabot, Jordi
A1 Gérard, Sébastien
A1 Vallecillo-Moreno, Antonio Jesús
K1 Incertidumbre (Teoría de la información)
K1 Ingeniería del software
AB There are numerous domains in which information systems need to deal with uncertain information. These uncertainties may originate from different reasons such as vagueness, imprecision, incompleteness or inconsistencies; and, in many cases, they cannot be neglected. In this paper, we are interested in representing and processing uncertain information in domain models, considering the stakeholders’ beliefs (opinions). We show how to associate beliefs to model elements, and how to propagate and operate with their associated uncertainty so that domain experts can individually reason about their models enriched with their personal opinions. In addition, we address the challenge of combining the opinions of different domain experts on the same model elements, with the goal to come up with informed collective decisions. We provide different strategies and a methodology to optimally merge individual opinions.
YR 2023
FD 2023
LK https://hdl.handle.net/10630/27652
UL https://hdl.handle.net/10630/27652
LA eng
NO This work is partially supported by Universidad de Málaga. Campus de Excelencia Internacional Andalucía Tech, the Spanish Government under projects LO-COSS (PID2020-114615RB-I00), CoSCA (PGC2018-094905-B-I00) and MBTI4A (P20-00067-FR); and TRANSACT, which has received funding from the ECSEL Joint Undertaking (JU) under grant agreement No 101007260. The JU receives support from the European Union’s Horizon 2020 research and innovation programme and Netherlands, Finland, Germany, Poland, Austria, Spain, Belgium, Denmark, and Norway.
DS RIUMA. Repositorio Institucional de la Universidad de Málaga
RD 21 ene 2026