RT Dissertation/Thesis
T1 Process-to-Text: A Framework for the Automatic Generation of Natural Language Descriptions of Processes
A1 Fontenla Seco, Yago
K1 Inteligencia Artificial
K1 Generación de Lenguaje Natural
K1 Minería de Procesos
K1 Procesos de Negocio
K1 Términos Lingüísticos Borrosos
AB Effectively presenting and comprehending processes is achallenging task. This thesis introduces different solutions forcommunicating process knowledge via natural language. Wepropose a taxonomy of relevant process descriptions based on afuzzy protoform model, validated by medical experts. Weintroduce the Process-to-Text framework, building on the Data-To-Text architecture, leverages process mining techniques in anontology-driven system using fuzzy logic, for the generation ofaccurate and contextually-aware process descriptions.Additionally, we introduce C-4PM, a conversational agent fordeclarative process mining, enhancing interaction andknowledge inference through natural language. This worksignifies a stride towards making process mining accessible andunderstandable for a broader audience.
YR 2024
FD 2024
LK http://hdl.handle.net/10347/33061
UL http://hdl.handle.net/10347/33061
LA eng
DS Minerva
RD 24 abr 2026