Demo Application for LETO: Learning Engine Through Ontologies

Suilan Estevez-Velarde, Andrés Montoyo, Yudivian Almeida-Cruz, Yoan Gutiérrez, Alejandro Piad-Morffis, Rafael Muñoz


Abstract
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.
Anthology ID:
R19-1032
Volume:
Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
Month:
September
Year:
2019
Address:
Varna, Bulgaria
Venue:
RANLP
SIG:
Publisher:
INCOMA Ltd.
Note:
Pages:
276–284
Language:
URL:
https://aclanthology.org/R19-1032
DOI:
10.26615/978-954-452-056-4_032
Bibkey:
Copy Citation:
PDF:
https://aclanthology.org/R19-1032.pdf