@inproceedings{estevez-velarde-etal-2019-demo,
title = "Demo Application for {LETO}: Learning Engine Through Ontologies",
author = "Estevez-Velarde, Suilan and
Montoyo, Andr{\'e}s and
Almeida-Cruz, Yudivian and
Guti{\'e}rrez, Yoan and
Piad-Morffis, Alejandro and
Mu{\~n}oz, Rafael",
editor = "Mitkov, Ruslan and
Angelova, Galia",
booktitle = "Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)",
month = sep,
year = "2019",
address = "Varna, Bulgaria",
publisher = "INCOMA Ltd.",
url = "https://aclanthology.org/R19-1032",
doi = "10.26615/978-954-452-056-4_032",
pages = "276--284",
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.",
}
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<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.</abstract>
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%0 Conference Proceedings
%T Demo Application for LETO: Learning Engine Through Ontologies
%A Estevez-Velarde, Suilan
%A Montoyo, Andrés
%A Almeida-Cruz, Yudivian
%A Gutiérrez, Yoan
%A Piad-Morffis, Alejandro
%A Muñoz, Rafael
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
%D 2019
%8 September
%I INCOMA Ltd.
%C Varna, Bulgaria
%F estevez-velarde-etal-2019-demo
%X 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.
%R 10.26615/978-954-452-056-4_032
%U https://aclanthology.org/R19-1032
%U https://doi.org/10.26615/978-954-452-056-4_032
%P 276-284
Markdown (Informal)
[Demo Application for LETO: Learning Engine Through Ontologies](https://aclanthology.org/R19-1032) (Estevez-Velarde et al., RANLP 2019)
ACL
- Suilan Estevez-Velarde, Andrés Montoyo, Yudivian Almeida-Cruz, Yoan Gutiérrez, Alejandro Piad-Morffis, and Rafael Muñoz. 2019. Demo Application for LETO: Learning Engine Through Ontologies. In Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019), pages 276–284, Varna, Bulgaria. INCOMA Ltd..