TY - GEN
T1 - Application of the LSA technique to determine the priority of alerts from a command and control center
AU - Orellana, Marcos
AU - Lima, Juan Fernando
AU - Game, Daniel Camacho
AU - León, Pablo Martinez
AU - Cedillo, Priscila
AU - Prado, Daniela
N1 - Publisher Copyright:
© 2021 IEEE.
PY - 2021/7/28
Y1 - 2021/7/28
N2 - It is essential to determine the alert level in a command-and-control center when someone calls an operator for an emergency since life may be in danger. The alert level is determined based on the evaluation that the operator can perceive during the call. Sometimes, cases can be similar to those previously attended. Therefore, it is helpful that this knowledge can be rescued and applied to new cases. In this context, the Latent Semantic Analysis (LSA) technique can determine the alert level and find the most representative words in each case. Thus, when a new alarm is triggered, the system can recommend the alert level with which it is rated. Consequently, a solution based on previous knowledge has been stated. This solution leads to the following methodological process: i) data preprocessing, ii) topic analysis and iii) classification. When this proposal was applied, the results revealed an accuracy greater than 60% in predicting the type of alert based on the text.
AB - It is essential to determine the alert level in a command-and-control center when someone calls an operator for an emergency since life may be in danger. The alert level is determined based on the evaluation that the operator can perceive during the call. Sometimes, cases can be similar to those previously attended. Therefore, it is helpful that this knowledge can be rescued and applied to new cases. In this context, the Latent Semantic Analysis (LSA) technique can determine the alert level and find the most representative words in each case. Thus, when a new alarm is triggered, the system can recommend the alert level with which it is rated. Consequently, a solution based on previous knowledge has been stated. This solution leads to the following methodological process: i) data preprocessing, ii) topic analysis and iii) classification. When this proposal was applied, the results revealed an accuracy greater than 60% in predicting the type of alert based on the text.
KW - Bag of Words
KW - Classification
KW - Pre-processing
KW - TF-IDF
UR - https://www.scopus.com/pages/publications/85117256805
U2 - 10.1109/ICEDEG52154.2021.9530965
DO - 10.1109/ICEDEG52154.2021.9530965
M3 - Contribución a la conferencia
AN - SCOPUS:85117256805
T3 - 2021 8th International Conference on eDemocracy and eGovernment, ICEDEG 2021
SP - 210
EP - 214
BT - 2021 8th International Conference on eDemocracy and eGovernment, ICEDEG 2021
A2 - Teran, Luis
A2 - Pincay, Jhonny
A2 - Portmann, Edy
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 8th International Conference on eDemocracy and eGovernment, ICEDEG 2021
Y2 - 28 July 2021 through 30 July 2021
ER -