AHCI RESEARCH GROUP
Publications
Papers published in international journals,
proceedings of conferences, workshops and books.
OUR RESEARCH
Scientific Publications
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You can use the tag cloud to select only the papers dealing with specific research topics.
You can expand the Abstract, Links and BibTex record for each paper.
2022
Cossentino, Massimo; Guastella, Davide; Lopes, Salvatore; Sabatucci, Luca; Tripiciano, Mario
Linguistic and Semantic Layers for Emergency Plans Journal Article
In: Intelligenza Artificiale, vol. 16, no. 1, pp. 7–25, 2022.
Abstract | Links | BibTeX | Tags: Emergency plans, Metamodel, Text to formal conversion
@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}
}
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.
Cossentino, Massimo; Guastella, Davide; Lopes, Salvatore; Sabatucci, Luca; Tripiciano, Mario
Linguistic and semantic layers for emergency plans Journal Article
In: Intelligenza Artificiale, vol. 16, no. 1, pp. 7–25, 2022.
Abstract | Links | BibTeX | Tags: Emergency plans, Metamodel, Text to formal conversion
@article{cossentino_linguistic_2022,
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. © 2022 - IOS Press. All rights reserved.},
keywords = {Emergency plans, Metamodel, Text to formal conversion},
pubstate = {published},
tppubtype = {article}
}
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. © 2022 - IOS Press. All rights reserved.
2021
Cossentino, Massimo; Lopes, Salvatore; Sabatucci, Luca; Tripiciano, Mario
Towards a Semantic Layer for Italian Emergency Plans. Proceedings Article
In: WOA, pp. 144–161, 2021.
Abstract | BibTeX | Tags: Domain knowledge, Emergency plans, Semantic layer, Text to formal conversion
@inproceedings{cossentinoSemanticLayerItalian2021,
title = {Towards a Semantic Layer for Italian Emergency Plans.},
author = { Massimo Cossentino and Salvatore Lopes and Luca Sabatucci and Mario Tripiciano},
year = {2021},
date = {2021-01-01},
booktitle = {WOA},
pages = {144--161},
abstract = {Emergency plans require a complex collaboration among multiple departments and roles. They are generally long textual documents containing practical instructions for hazard responses in natural language. This work focuses on converting informal documents to a more rigorous structured-text representation by taking advantage of well-known techniques from the literature. However, this task is costly, it requires technical skills and sound domain knowledge, and it is entirely subjective. To this aim, we propose a semantic layer that supports the formalization of an emergency plan by identifying essential elements of the input document and highlighting inconsistencies, redundancies, and ambiguities. textcopyright 2021 CEUR-WS. All rights reserved.},
keywords = {Domain knowledge, Emergency plans, Semantic layer, Text to formal conversion},
pubstate = {published},
tppubtype = {inproceedings}
}
Emergency plans require a complex collaboration among multiple departments and roles. They are generally long textual documents containing practical instructions for hazard responses in natural language. This work focuses on converting informal documents to a more rigorous structured-text representation by taking advantage of well-known techniques from the literature. However, this task is costly, it requires technical skills and sound domain knowledge, and it is entirely subjective. To this aim, we propose a semantic layer that supports the formalization of an emergency plan by identifying essential elements of the input document and highlighting inconsistencies, redundancies, and ambiguities. textcopyright 2021 CEUR-WS. All rights reserved.
Cossentino, Massimo; Lopes, Salvatore; Sabatucci, Luca; Tripiciano, Mario
Towards a Semantic Layer for Italian Emergency Plans. Proceedings Article
In: WOA, pp. 144–161, 2021.
Abstract | Links | BibTeX | Tags: Domain knowledge, Emergency plans, Semantic layer, Text to formal conversion
@inproceedings{cossentino_towards_2021,
title = {Towards a Semantic Layer for Italian Emergency Plans.},
author = {Massimo Cossentino and Salvatore Lopes and Luca Sabatucci and Mario Tripiciano},
url = {https://ceur-ws.org/Vol-2963/paper9.pdf},
year = {2021},
date = {2021-01-01},
booktitle = {WOA},
pages = {144–161},
abstract = {Emergency plans require a complex collaboration among multiple departments and roles. They are generally long textual documents containing practical instructions for hazard responses in natural language. This work focuses on converting informal documents to a more rigorous structured-text representation by taking advantage of well-known techniques from the literature. However, this task is costly, it requires technical skills and sound domain knowledge, and it is entirely subjective. To this aim, we propose a semantic layer that supports the formalization of an emergency plan by identifying essential elements of the input document and highlighting inconsistencies, redundancies, and ambiguities. © 2021 CEUR-WS. All rights reserved.},
keywords = {Domain knowledge, Emergency plans, Semantic layer, Text to formal conversion},
pubstate = {published},
tppubtype = {inproceedings}
}
Emergency plans require a complex collaboration among multiple departments and roles. They are generally long textual documents containing practical instructions for hazard responses in natural language. This work focuses on converting informal documents to a more rigorous structured-text representation by taking advantage of well-known techniques from the literature. However, this task is costly, it requires technical skills and sound domain knowledge, and it is entirely subjective. To this aim, we propose a semantic layer that supports the formalization of an emergency plan by identifying essential elements of the input document and highlighting inconsistencies, redundancies, and ambiguities. © 2021 CEUR-WS. All rights reserved.