Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Minghua Nuo"'
Publikováno v:
2021 International Conference on High Performance Big Data and Intelligent Systems (HPBD&IS).
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::76bddd3aa5bdf2c54f60476d391c5398
https://doi.org/10.1109/hpbdis53214.2021.9658455
https://doi.org/10.1109/hpbdis53214.2021.9658455
Publikováno v:
CIS
Attribute extraction is a very significant and fundamental task of Natural Language Processing (NLP). It aims to extract missing attribute knowledge for entities from unstructured contexts. Attribute knowledge is an important part of the knowledge gr
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2b21c82acfd40f3e1dd1a8edcc2adc35
https://doi.org/10.1109/cis.2019.00031
https://doi.org/10.1109/cis.2019.00031
Publikováno v:
Natural Language Understanding and Intelligent Applications ISBN: 9783319504957
NLPCC/ICCPOL
NLPCC/ICCPOL
This paper presents an identification framework for extracting Tibetan multi-word expressions. The framework includes two phases. In the first phase, sentences are segmented and high-frequency word-based n-grams are extracted using Nagao’s N-gram s
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::0c33acb93bda9ec4f93c8160823f128e
https://doi.org/10.1007/978-3-319-50496-4_2
https://doi.org/10.1007/978-3-319-50496-4_2
Publikováno v:
ACL (2)
In Tibetan, as words are written consecutively without delimiters, finding unknown word boundary is difficult. This paper presents a hybrid approach for Tibetan unknown word identification for offline corpus processing. Firstly, Tibetan named entity
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::07eb687f90f5cf5cbc7098f1d24241d0
https://doi.org/10.3115/v1/p15-2074
https://doi.org/10.3115/v1/p15-2074
Publikováno v:
IALP
This paper aims to construct Chinese-Tibetan multi-word equivalent pair dictionary for Chinese-Tibetan computer-aided translation system. Since Tibetan is a morphologically rich language, we propose two-phase framework to automatically extract multi-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::485848a3d4d9c8e290e2e8905158884e
https://doi.org/10.1109/ialp.2011.33
https://doi.org/10.1109/ialp.2011.33
Publikováno v:
Himalayan Linguistics; 2016, Vol. 15 Issue 1, p149-166, 19p