Demo Application for LETO: Learning Engine Through Ontologies
| Autor: | Suilan Estevez-Velarde, Yoan Gutiérrez, Andrés Montoyo, Alejandro Piad-Morffis, Rafael Muñoz, Yudivián Almeida-Cruz |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
business.industry
Computer science Unstructured data 02 engineering and technology computer.software_genre World Wide Web 020204 information systems 0202 electrical engineering electronic engineering information engineering Leverage (statistics) 020201 artificial intelligence & image processing The Internet Software system Artificial intelligence Architecture business Relevant information computer Natural language processing |
| Zdroj: | RANLP |
| DOI: | 10.26615/978-954-452-056-4_032 |
| Popis: | The massive amount of multi-formatted information available on the Web necessitates the design of software systems that leverage this information to obtain knowledge that is valid and useful. The main challenge is to discover relevant information and continuously update, enrich and integrate knowledge from various sources of structured and unstructured data. This paper presents the Learning Engine Through Ontologies(LETO) framework, an architecture for the continuous and incremental discovery of knowledge from multiple sources of unstructured and structured data. We justify the main design decision behind LETO’s architecture and evaluate the framework’s feasibility using the Internet Movie Data Base(IMDB) and Twitter as a practical application. |
| Databáze: | OpenAIRE |
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