Zobrazeno 1 - 7
of 7
pro vyhledávání: '"David Pinto Avendaño"'
Publikováno v:
Research in Computing Science. 147:45-52
Autor:
Gabriela Ramírez-de-la-Rosa, David Pinto-Avendaño, Esaú Villatoro-Tello, Héctor Jiménez Salazar, Christian Sánchez-Sánchez
Publikováno v:
Research in Computing Science. 144:83-96
Publikováno v:
Scopus-Elsevier
This paper focuses on the task of bilingual clustering, which involves dividing a set of documents from two different languages into a set of groups, so that documents with similar topics belong to the same group, regardless of their source language.
Autor:
María Beatríz Bernábe Loranca, David Pinto Avendaño, Ruiz-Vanoye, Jorge A., José Espinosa Rosales, Elias Olivares-Benitez
Publikováno v:
Benemérita Universidad Autónoma de Puebla
BUAP
Redalyc-BUAP
Redalyc
BUAP
Redalyc-BUAP
Redalyc
As part of the process to support decision making in population problems, with the aim of promoting the selection of projects with funding support for the sector of the economically inactive population, in this paper a custom multi-objective method w
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::bbf7b2d2f43ab7e9ffea39f40c62dcf7
http://www.redalyc.org/articulo.oa?id=265224466007
http://www.redalyc.org/articulo.oa?id=265224466007
Autor:
Manuel Montes-y-Gómez, Luis Villaseñor-Pineda, David Pinto-Avendaño, Thamar Solorio, Gabriela Ramírez-de-la-Rosa
Publikováno v:
Advances in Natural Language Processing ISBN: 9783642147692
IceTAL
IceTAL
Crosslingual text classification consists of exploiting labeled documents in a source language to classify documents in a different target language. In addition to the evident translation problem, this task also faces some difficulties caused by the
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ed5617651a61cbe3b8d87152fc48909e
https://doi.org/10.1007/978-3-642-14770-8_34
https://doi.org/10.1007/978-3-642-14770-8_34
Publikováno v:
2009 Eighth Mexican International Conference on Artificial Intelligence.
Multi-document summarization systems must be able to draw the "best" information from a set of documents.In this paper we propose a novel extractive approach for multidocument summarization based on the detection of locally relevant sentences. Our ma
Autor:
Luis Villaseñor-Pineda, David Pinto-Avendaño, Paolo Rosso, Rafael Guzmán-Cabrera, Manuel Montes-y-Gómez
Publikováno v:
Computational Linguistics and Intelligent Text Processing ISBN: 9783642003813
CICLing
CICLing
As any other classification task, Word Sense Disambiguation requires a large number of training examples. These examples, which are easily obtained for most of the tasks, are particularly difficult to obtain for this case. Based on this fact, in this
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::23419eeb0231885f5d6a94490263103b
https://doi.org/10.1007/978-3-642-00382-0_21
https://doi.org/10.1007/978-3-642-00382-0_21