A probabilistic algorithm to predict missing facts from knowledge graphs
| dc.creator | André Lopes Gonzaga | |
| dc.date.accessioned | 2020-10-27T18:01:40Z | |
| dc.date.accessioned | 2025-09-09T01:04:35Z | |
| dc.date.available | 2020-10-27T18:01:40Z | |
| dc.date.issued | 2019-01-31 | |
| dc.identifier.uri | https://hdl.handle.net/1843/34314 | |
| dc.language | eng | |
| dc.publisher | Universidade Federal de Minas Gerais | |
| dc.rights | Acesso Aberto | |
| dc.subject.other | Knowledge | |
| dc.subject.other | Graph | |
| dc.subject.other | Probabilistic | |
| dc.subject.other | Learning | |
| dc.subject.other | Computação – Teses | |
| dc.subject.other | Web semântica – Teses | |
| dc.subject.other | Aprendizado do computador – Teses | |
| dc.subject.other | Base de conhecimento – Teses | |
| dc.subject.other | Predição de falhas – Teses | |
| dc.title | A probabilistic algorithm to predict missing facts from knowledge graphs | |
| dc.title.alternative | Um algoritmo probabilístico para predição de fatos em grafos de conhecimento | |
| dc.type | Dissertação de mestrado | |
| local.contributor.advisor-co1 | Mario Sérgio Ferreira Alvim Júnior | |
| local.contributor.advisor1 | Mirella Mouro Moro | |
| local.contributor.advisor1Lattes | http://lattes.cnpq.br/6408321790990372 | |
| local.contributor.referee1 | Luiz Chaimowicz | |
| local.contributor.referee1 | Denilson Barbosa | |
| local.creator.Lattes | http://lattes.cnpq.br/1442335031987693 | |
| local.description.resumo | Knowledge Graph, as the name says, is a way to represent knowledge using a directed graph structure (nodes and edges). However, such graphs are often incomplete or contain a considerable amount of wrong facts. This work presents ProA: a probabilistic algorithm to predict missing facts from Knowledge Graphs based on the probability distribution over paths between entities. Compared to current state-of-the-art approaches, ProA has the following advantages: simplicity as it considers only the topological structure of a knowledge graph, good performance as it does not require any complex calculations, and readiness as it has no other requirement but the graph itself. | |
| local.publisher.country | Brasil | |
| local.publisher.department | ICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO | |
| local.publisher.initials | UFMG | |
| local.publisher.program | Programa de Pós-Graduação em Ciência da Computação |