A Method to obtain a Knowledge Representation from a Natural Language Specification of the Domain using the Glossary LEL
| cic.institucionOrigen | Laboratorio de Investigación y Formación en Informática Avanzada (LIFIA) | |
| cic.isFulltext | SI | |
| cic.isPeerReviewed | SI | |
| cic.lugarDesarrollo | Laboratorio de Investigación y Formación en Informática Avanzada (LIFIA) | |
| cic.parentType | Objeto de conferencia | |
| cic.version | Aceptada | |
| dc.date.accessioned | 2023-12-21T12:02:35Z | |
| dc.date.available | 2023-12-21T12:02:35Z | |
| dc.identifier.uri | https://digital.cic.gba.gob.ar/handle/11746/12152 | |
| dc.title | A Method to obtain a Knowledge Representation from a Natural Language Specification of the Domain using the Glossary LEL | en |
| dc.type | Documento de conferencia | |
| dcterms.abstract | Good requirements (correct, consistent, unambiguous, etc.) are crucial to software development success. Errors made in the requirements stage can cost up to 200 times if they are discovered once the software is delivered to the client. Natural language artifacts are the most used tool to write requirements, since they are understandable by the both parties that participate in the software development: the stakeholders and the development team. Nevertheless, natural language can introduce many defects (ambiguity, vagueness, generality, etc.). Formal reasoning is a good strategy to check whether requirements satisfy the attributes of good requirements or not, but formal reasoning cannot be applied to natural language specification with defects. Thus, this paper proposes an approach to write a good specification and obtain knowledge from it. The approach uses a particular lexicon, the glossary LEL, and it suggest guidelines to write good specification, and it also suggest rules to obtain knowledge (concepts and relations) from the glossary LEL. The paper also presents a prototype to assist to this approach, and a preliminary evaluation of the approach. | en |
| dcterms.creator.author | Antonelli, Leandro | |
| dcterms.creator.author | Lezoche, Mario | |
| dcterms.creator.author | Delle Ville, Juliana | |
| dcterms.isPartOf.series | Decisioning 2023. The second workshop on Collaboration in knowledge discovery and decision making (Popayán, Colombia 21 al 23 de junio de 2023) | |
| dcterms.issued | 2023-06 | |
| dcterms.language | Inglés | |
| dcterms.license | Attribution-NonCommercial-ShareAlike 4.0 International (BY-NC-SA 4.0) | |
| dcterms.subject | Requirements specification | en |
| dcterms.subject | knowledge representation | en |
| dcterms.subject | natural language | en |
| dcterms.subject | artificial intelligence | en |
| dcterms.subject.materia | Ciencias de la Computación e Información |
Archivos
Bloque original
1 - 1 de 1
Cargando...
- Nombre:
- A Method to obtain a Knowledge Representation.pdf-PDFA.pdf
- Tamaño:
- 688.52 KB
- Formato:
- Adobe Portable Document Format
- Descripción:
- Documento completo
Bloque de licencias
1 - 1 de 1
Cargando...
- Nombre:
- license.txt
- Tamaño:
- 3.46 KB
- Formato:
- Item-specific license agreed upon to submission
- Descripción: