Zobrazeno 1 - 10
of 297
pro vyhledávání: '"Lexical chain"'
Akademický článek
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Autor:
Euisok Chung, Jeon Gue Park
Publikováno v:
ETRI Journal, Vol 39, Iss 4, Pp 455-466 (2017)
This study focuses on a method for sequential data augmentation in order to alleviate data sparseness problems. Specifically, we present corpus expansion techniques for enhancing the coverage of a language model. Recent recurrent neural network studi
Externí odkaz:
https://doaj.org/article/2783d2c5ac17465caa8a35ab86efb419
Autor:
Tatiana Kaushinis, Alexander Kirillov, Nikita Korzhitsky, Andrew Krizhanovsky, Aleksander Pilinovich, Irina Sikhonina, Anna Spirkova, Valentina Starkova, Tatiana Stepkina, Stanislav Tkach, Julia Chirkova, Alexey Chuharev, Daria Shorets, Daria Yankevich, Ekaterina Yaryshkina
Publikováno v:
Transactions of the Karelian Research Centre of the Russian Academy of Sciences, Iss 10, Pp 69-98 (2015)
The word-sense disambiguation task is a classification task, where the goal is to predict the meaning of words and phrases with the help of surrounding text. The purpose of this short review is to acquaint the reader with the general directions of wo
Externí odkaz:
https://doaj.org/article/b5c1a0953b8d45028d96eb95e217781f
Kniha
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Autor:
Wafaa Al-Hameed, Marwan B. Mohammed
The clustering analysis techniques play an important role in the area of data mining. Although from existence several clustering techniques. However, it still to their tries to improve the clustering process efficiently or propose new techniques seek
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ff826f1a3ecda3c9a090b73ba37a2710
https://zenodo.org/record/7115236
https://zenodo.org/record/7115236
Publikováno v:
IEEE Journal of Biomedical and Health Informatics. 23:2164-2173
Our goal is data-driven discovery of features for text simplification. In this work, we investigate three types of lexical chains: exact, synonymous, and semantic. A lexical chain links semantically related words in a document. We examine their poten
Publikováno v:
MATEC Web of Conferences, Vol 100, p 02059 (2017)
Event relation recognition, as one of natural language processing technologies, faces information stream of texts detecting event relation. By analyzing the influence of the words of different parts of speech on the relevance of events. And use the f
Externí odkaz:
https://doaj.org/article/b83337a63bc84fe1a10323ca067fc23c
Autor:
Bonnie J. Dorr
Publikováno v:
Lexical Acquisition: Exploiting
Resources to Build a Lexicon ISBN: 9781315785387
Resources to Build a Lexicon ISBN: 9781315785387
This report describes the organization and content of lexical information required for the task of machine translation. In particular, the lexical- conceptual basis for UNITRAN, an implemented machine translation system, will be described. UNITRAN us
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cbe99c4e2cb383a6ee90b12ee600147f
https://doi.org/10.4324/9781315785387-14
https://doi.org/10.4324/9781315785387-14
Autor:
William I. Grosky, Debora Maria Rossi de Medeiros, Terry Ruas, Fabrício Olivetti de França, Charles Henrique Porto Ferreira
The relationship between words in a sentence often tells us more about the underlying semantic content of a document than its actual words, individually. In this work, we propose two novel algorithms, called Flexible Lexical Chain II and Fixed Lexica
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8d8b25a797065c01f9e59332ae114613
http://arxiv.org/abs/2101.09023
http://arxiv.org/abs/2101.09023
Publikováno v:
Lecture Notes on Data Engineering and Communications Technologies ISBN: 9783030707125
The amount of text data is continuously increasing both at online and offline storage, that makes is difficult for people to read across and find the desired information within a possible available time. This necessitate the use of technique such as
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::94ad7b3b11897f7c5902606bacac7496
https://doi.org/10.1007/978-3-030-70713-2_41
https://doi.org/10.1007/978-3-030-70713-2_41