Knowledge Graph Prediction using Negative Statements: an Approach Based on Entity-nearest Neighbor Count Algorithm

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AudienciaPúblico en generales_ES
CoberturaMéxico[ 143]es_ES
Fecha de ingreso2026-10-05T16:35:00Z
Fecha de publicación2024-01-01
ResumenThis paper presents our contribution to knowledge graph predictions using negative statements (NEGKNOW) challenge. This contribution consists of the definition of the Entity-nearest Neighbor Count (E-NNC) Algorithm. In this algorithm, we consider that if two entities are in relation, then, they linked to least one common entity. The list of common entities between two entities are called their common neighbors. Thus, the algorithm calculates the common neighbor between two entities. The E-NNC algorithm defined in this work was applied for the three tasks of the NEGKNOW challenge. These tasks consists of predicting if there is an interaction between two proteins (Task A), a protein and a disease (Task B) and a gene and a disease (Task C). The organizers of this challenge provided the train and the test set. The algorithm assessed on the train set to evaluate its performance. For task A, the algorithm proves to be powerful because we obtained an accuracy of 0.9. For Task B, an accuracy of 0.9 and 0.5 for task C.es_ES
URIhttps://riuat.uat.edu.mx/handle/123456789/6473
IdiomaInglés[20]es_ES
EditorialCEUR-WSes_ES
RelaciónCEUR Workshop Proceedingses_ES
URL relacionadohttps://www.scopus.com/pages/publications/105003726015?origin=resultslistes_ES
DerechosAcceso restringido / Suscripción (Metadatos de producción científica)es_ES
Licenciahttp://purl.org/coar/access_right/c_16eces_ES
FuenteCEUR Workshop Proceedings
Palabra claveEntity-nearest Neighbor Countes_ES
Palabra claveKnowledge Graphes_ES
Palabra claveKnowledge Graph Completiones_ES
Palabra claveRelation Predictiones_ES
TítuloKnowledge Graph Prediction using Negative Statements: an Approach Based on Entity-nearest Neighbor Count Algorithmes_ES
TipoPonenciaes_ES
ArbitradoHa sido Arbitradoes_ES
AutorTeguimene, Furel D.
AutorAzanzi, Jiomekong
AutorTiwari, Sanju
AutorCamara, Gaoussou
AutorTeguimene, Furel D.es_ES
AutorAzanzi, Jiomekonges_ES
AutorTiwari, Sanjues_ES
AutorCamara, Gaoussoues_ES
InstituciónUniversidad Autónoma de Tamaulipas
InstituciónUniversidad Autónoma de Tamaulipases_ES
Rango de páginas53-61es_ES
URL relacionadahttps://www.scopus.com/pages/publications/105003726015?origin=resultslist
Tipo de artículoIndexado
Tipo de artículoIndexadoes_ES
Volumen3952es_ES

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