Publications

@article{cossentinoLinguisticSemanticLayers2022,

title = {Linguistic and Semantic Layers for Emergency Plans},

author = { Massimo Cossentino and Davide Guastella and Salvatore Lopes and Luca Sabatucci and Mario Tripiciano},

doi = {10.3233/IA-210122},

year  = {2022},

date = {2022-01-01},

journal = {Intelligenza Artificiale},

volume = {16},

number = {1},

pages = {7--25},

abstract = {Plans for emergency response are complex collaborations in which actors take roles and responsibilities. They are generally long textual documents containing practical instructions, in natural language, for hazard responses. A more rigorous structured-text would be useful for a twofold audience. From one side, it can be useful for quickly understanding the plan and on the other side it can be used to improve the modelling phase and delivering an automatic emergency-support system. This paper proposes an approach, conceived for humans, for converting a free-form plan document into a structured version of the same document. The approach is based on a linguistic and semantic analysis that are strictly correlated and materialize in a metamodel. It contains the essential elements of an emergency plan, and it aids in interpreting the input document also reducing inconsistencies, redundancies, and ambiguities. textcopyright 2022 - IOS Press. All rights reserved.},

keywords = {Emergency plans, Metamodel, Text to formal conversion},

pubstate = {published},

tppubtype = {article}

}