Multi-view learning for hierarchical topic detection on corpus of documents
| dc.contributor.advisor | Niño Vasquez, Luis Fernando | |
| dc.contributor.author | Calero Espinosa, Juan Camilo | |
| dc.contributor.researchgroup | LABORATORIO DE INVESTIGACIÓN EN SISTEMAS INTELIGENTES - LISI | spa |
| dc.date.accessioned | 2021-05-26T16:54:28Z | |
| dc.date.available | 2021-05-26T16:54:28Z | |
| dc.date.issued | 2021 | |
| dc.description | diagramas, ilustraciones a color, tablas | spa |
| dc.description.abstract | Topic detection on a large corpus of documents requires a considerable amount of computational resources, and the number of topics increases the burden as well. However, even a large number of topics might not be as specific as desired, or simply the topic quality starts decreasing after a certain number. To overcome these obstacles, we propose a new methodology for hierarchical topic detection, which uses multi-view clustering to link different topic models extracted from document named entities and part of speech tags. Results on three different datasets evince that the methodology decreases the memory cost of topic detection, improves topic quality and allows the detection of more topics. | eng |
| dc.description.abstract | La detección de temas en grandes colecciones de documentos requiere una considerable cantidad de recursos computacionales, y el número de temas también puede aumentar la carga computacional. Incluso con un elevado nùmero de temas, estos pueden no ser tan específicos como se desea, o simplemente la calidad de los temas comienza a disminuir después de cierto número. Para superar estos obstáculos, proponemos una nueva metodología para la detección jerárquica de temas, que utiliza agrupamiento multi-vista para vincular diferentes modelos de temas extraídos de las partes del discurso y de las entidades nombradas de los documentos. Los resultados en tres conjuntos de documentos muestran que la metodología disminuye el costo en memoria de la detección de temas, permitiendo detectar màs temas y al mismo tiempo mejorar su calidad. | spa |
| dc.description.degreelevel | Maestría | spa |
| dc.description.degreename | Magíster en Ingeniería – Sistemas y Computación | spa |
| dc.description.researcharea | Procesamiento de lenguaje natural | spa |
| dc.format.extent | 1 recurso en línea (88 páginas) | spa |
| dc.format.mimetype | application/pdf | spa |
| dc.identifier.instname | Universidad Nacional de Colombia | spa |
| dc.identifier.reponame | Repositorio Institucional Universidad Nacional de Colombia | spa |
| dc.identifier.repourl | https://repositorio.unal.edu.co/ | spa |
| dc.identifier.uri | https://repositorio.unal.edu.co/handle/unal/79567 | |
| dc.language.iso | eng | spa |
| dc.publisher | Universidad Nacional de Colombia | spa |
| dc.publisher.branch | Universidad Nacional de Colombia - Sede Bogotá | spa |
| dc.publisher.department | Departamento de Ingeniería de Sistemas e Industrial | spa |
| dc.publisher.faculty | Facultad de Ingeniería | spa |
| dc.publisher.place | Bogotá | spa |
| dc.publisher.program | Bogotá - Ingeniería - Maestría en Ingeniería - Ingeniería de Sistemas y Computación | spa |
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| dc.rights.accessrights | info:eu-repo/semantics/openAccess | spa |
| dc.rights.license | Reconocimiento 4.0 Internacional | spa |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | spa |
| dc.subject.ddc | 000 - Ciencias de la computación, información y obras generales | spa |
| dc.subject.proposal | Named entities | eng |
| dc.subject.proposal | Topic detection | eng |
| dc.subject.proposal | Multi-view clustering | eng |
| dc.subject.proposal | Multi-view learning | eng |
| dc.subject.proposal | Graph fusion | eng |
| dc.subject.proposal | Entidades nombradas | spa |
| dc.subject.proposal | Aprendizaje multi-vista | spa |
| dc.subject.proposal | Agrupamiento multi-vista | spa |
| dc.subject.proposal | Fusión de grafos | spa |
| dc.subject.unesco | Indexación automática | |
| dc.subject.unesco | Recuperación de información | |
| dc.subject.unesco | Information processing | |
| dc.subject.unesco | Automatic indexing | |
| dc.title | Multi-view learning for hierarchical topic detection on corpus of documents | eng |
| dc.title.translated | Aprendizaje multi-vista para la detección jerárquica de temas en corpus de documentos | spa |
| dc.type | Trabajo de grado - Maestría | spa |
| dc.type.coar | http://purl.org/coar/resource_type/c_bdcc | spa |
| dc.type.coarversion | http://purl.org/coar/version/c_ab4af688f83e57aa | spa |
| dc.type.content | Text | spa |
| dc.type.driver | info:eu-repo/semantics/masterThesis | spa |
| dc.type.redcol | http://purl.org/redcol/resource_type/TM | spa |
| dc.type.version | info:eu-repo/semantics/acceptedVersion | spa |
| oaire.accessrights | http://purl.org/coar/access_right/c_abf2 | spa |
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