Zobrazeno 1 - 8
of 8
pro vyhledávání: '"Julio Javier Castillo"'
Autor:
María del Carmen Rojas, Juan Carlos Vázquez, Izabelle Vianna de Vasconcellos, Julio Javier Castillo, Marco Lobo, Simone Cynamon Cohen, Francisco Berardo
Publikováno v:
Saúde e Sociedade, Vol 24, Iss 4, Pp 1244-1256 (2015)
Este estudio se desarrolla en el marco de la Red Interamericana de Vivienda Saludable, avalada por la OPS/OMS, y surge de la necesidad de fortalecer los sistemas nacionales y locales de vigilancia en salud ambiental con el fin de reconocer las desigu
Externí odkaz:
https://doaj.org/article/f3297a9a5777489a9ce78149210a2a3b
Publikováno v:
Polibits. 44:67-72
In this paper, we show an approach to cross–lingual textual entailment (CLTE) by using machine translation systems such as Bing Translator and Google Translate. We experiment with a wide variety of data sets to the task of textual Entailment (TE) a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::38a2e783b215fa6a3946514857977079
https://doi.org/10.17562/pb-44-10
https://doi.org/10.17562/pb-44-10
Autor:
Julio Javier Castillo
Publikováno v:
International Journal of Machine Learning and Cybernetics. 2:177-189
In this paper we explain how to build a recognizing textual entailment (RTE) system which only uses semantic similarity measures based on WordNet. We show how the widely used WordNet-based semantic measures can be generalized to build sentence level
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f8ed07860eb804ccc721edc24a19a57c
https://doi.org/10.1007/s13042-011-0026-z
https://doi.org/10.1007/s13042-011-0026-z
Autor:
Julio Javier Castillo
Publikováno v:
2010 International Conference on Intelligent Computing and Cognitive Informatics.
In this work we present our initial approach to the Recognizing Textual Entailment Search Pilot Task proposed by NIST. We proposed a new algorithm to address Text Entailment task to a document level making use of coreference resolution and then reduc
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ff1408cb2cde838dcc0d2429d5a1d753
https://doi.org/10.1109/icicci.2010.84
https://doi.org/10.1109/icicci.2010.84
Autor:
Julio Javier Castillo
Publikováno v:
Advances in Intelligent and Soft Computing ISBN: 9783642148828
DCAI
DCAI
This paper presents how the size of Textual Entailment Corpus could be increased by using Translators to generate additional 〈t, h〉 pairs. Also, we show the theoretical upper bound of a Corpus expanded by translators. Then, we propose an algorith
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::54ebcd500b716e6996b386fdbb182603
https://doi.org/10.1007/978-3-642-14883-5_25
https://doi.org/10.1007/978-3-642-14883-5_25
Autor:
Julio Javier Castillo
Publikováno v:
Advances in Artificial Intelligence ISBN: 9783642167607
MICAI (1)
MICAI (1)
In this paper, we present a Recognizing Textual Entailment system which uses semantic similarity metrics to sentence level only using WordNet as source of knowledge. We show how the widely used semantic measures Word-Net-based can be generalized to b
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2913efa96759c1fab3851e7f660110c2
https://doi.org/10.1007/978-3-642-16761-4_5
https://doi.org/10.1007/978-3-642-16761-4_5
Publikováno v:
Advances in Artificial Intelligence – IBERAMIA 2010 ISBN: 9783642169519
IBERAMIA
IBERAMIA
This paper presents a Recognizing Textual Entailment system which uses semantic distances to sentence level over WordNet to assess the impact on predicting Textual Entailment datasets. We extent word-to-word metrics to sentence level in order to best
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::8163980274d66716fcbc437beb82d859
https://doi.org/10.1007/978-3-642-16952-6_37
https://doi.org/10.1007/978-3-642-16952-6_37
Autor:
Julio Javier Castillo
Publikováno v:
Advances in Natural Language Processing ISBN: 9783642147692
IceTAL
IceTAL
This paper explores how to increase the size of Textual Entailment Corpus by using Machine Translation systems to generate additional 〈t,h〉 pairs. We also analyze the theoretical upper bound of a Corpus expanded by machine translation systems, an
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::1ae5975565ded5339daf53349b1a5679
https://doi.org/10.1007/978-3-642-14770-8_12
https://doi.org/10.1007/978-3-642-14770-8_12