A knowledge-based approach to information retrieval in collections of textual documents of the biomedical domain

Abstract The exponential growth in the amount of available data has posed new challenges to re- searchers. Search on such amount of data is a difficult task which turns even harder when the data belongs to a specific domain which has its own terminology and requires some background knowledge. Tradit...

Full description

Autores:
Riveros Cruz, Luis Alejandro
Tipo de recurso:
Fecha de publicación:
2015
Institución:
Universidad Nacional de Colombia
Repositorio:
Universidad Nacional de Colombia
Idioma:
spa
OAI Identifier:
oai:repositorio.unal.edu.co:unal/54814
Acceso en línea:
https://repositorio.unal.edu.co/handle/unal/54814
http://bdigital.unal.edu.co/49994/
Palabra clave:
02 Bibliotecología y ciencias de la información / Library and information sciences
6 Tecnología (ciencias aplicadas) / Technology
62 Ingeniería y operaciones afines / Engineering
Information retrieval
Ontology
Nowledge bases
Búsqueda de información
Ontología
Rights
openAccess
License
Atribución-NoComercial 4.0 Internacional
Description
Summary:Abstract The exponential growth in the amount of available data has posed new challenges to re- searchers. Search on such amount of data is a difficult task which turns even harder when the data belongs to a specific domain which has its own terminology and requires some background knowledge. Traditional information retrieval systems are based on keywords. In this kind of systems the output for a given query is a ranking of the documents that match the keywords. This model works well in scenarios with few documents or if the system achieves a high perfor- mance ensuring that the first results contain the most relevant documents. However, in most cases the collections are huge and the retrieval results are an endless list of documents that must be scanned manually. This work proposes an information retrieval approach which incorporates domain specific knowledge from an ontology within the traditional information retrieval model in order to overcome some of its limitations. The domain knowledge is used to add semantic capabili- ties and to provide the user with an enriched interface which includes metadata about the retrieved results, thus facilitating its exploration and filtering