Modelo semántico de expansión de consultas para la búsqueda web (MSEC)
Internet has become the largest repository of human knowledge, and the amount of stored information increases day by day. This increase of information affects the levels of precision reported by Web search engines regarding documents retrieved for the user. One strategy being used to addre...
- Autores:
- Tipo de recurso:
- Fecha de publicación:
- 2012
- Institución:
- Universidad Industrial de Santander
- Repositorio:
- Repositorio UIS
- Idioma:
- spa
- OAI Identifier:
- oai:noesis.uis.edu.co:20.500.14071/8227
- Acceso en línea:
- https://revistas.uis.edu.co/index.php/revistauisingenierias/article/view/11-20
https://noesis.uis.edu.co/handle/20.500.14071/8227
- Palabra clave:
- Web Search
query expansion
domain ontologies
user profiles
semantic similarity
Búsqueda Web
expansión de consulta
ontologías de dominio
perfiles de usuario
similitud semántica
- Rights
- openAccess
- License
- Attribution-NonCommercial 4.0 International (CC BY-NC 4.0)
| Summary: | Internet has become the largest repository of human knowledge, and the amount of stored information increases day by day. This increase of information affects the levels of precision reported by Web search engines regarding documents retrieved for the user. One strategy being used to address this problem is a focus on a personalized resource recovery. Several projects currently offer semantic methods for improving the relevance of search results through the use of ontologies, natural language processing, knowledge based systems, query specification languages, and user profile, among others. Results are generally better than for web search engines that do not use these techniques. However, the high cost of these improvements in precision relate to use of more complex algorithms in carrying out the search and which are more wasteful of computational resources. This article describes a semantic query expansion model called MSEC, which is based mostly on the concept of semantic similarity, starting from domain ontologies and on the use of user profile in order to customize user searches so to improve their precision. In order to evaluate the proposed model, a software prototype was created. Preliminary experimental results show an improvement compared to the traditional web search approach. Finally the model was compared against the best state of the art semantic search engine, called GoPubMed, for the MEDLINE collection. |
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