Zobrazeno 1 - 10
of 24
pro vyhledávání: '"Hiromi Amano"'
Publikováno v:
SN Applied Sciences, Vol 4, Iss 3, Pp 1-16 (2022)
Abstract In previous studies, we have treated real written texts as time series data and have tried to investigate dynamic correlations of word occurrences by utilizing autocorrelation functions (ACFs) and also by simulation of pseudo-text synthesis.
Externí odkaz:
https://doaj.org/article/d23bca614b9744ea9acae69bf7d90d75
Publikováno v:
Entropy, Vol 24, Iss 7, p 858 (2022)
It has been clarified that words in written texts are classified into two groups called Type-I and Type-II words. The Type-I words are words that exhibit long-range dynamic correlations in written texts while the Type-II words do not show any type of
Externí odkaz:
https://doaj.org/article/690aa81444394e4cbb6a290bff7d27ef
Publikováno v:
Journal of Data Analysis and Information Processing. :46-73
In this study, we regard written texts as time series data and try to investigate dynamic correlations of word occurrences by utilizing an autocorrelation function (ACF). After defining appropriate formula for the ACF that is suitable for expressing
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::14daa15909ff160343919354f597e526
https://doi.org/10.4236/jdaip.2019.72004
https://doi.org/10.4236/jdaip.2019.72004
Publikováno v:
Journal of Data Analysis and Information Processing. :228-249
In a previous study, we introduced dynamical aspects of written texts by regarding serial sentence number from the first to last sentence of a given text as discretized time. Using this definition of a textual timeline, we defined an autocorrelation
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::cbc9f1f0eff25962d9822fa1bf08e53b
https://doi.org/10.4236/jdaip.2019.74014
https://doi.org/10.4236/jdaip.2019.74014
Publikováno v:
SN Applied Sciences. 2
In a previous study, we have regarded real written texts as time series data and have tried to investigate dynamic correlations of word occurrences by utilizing an autocorrelation function (ACF). The results showed that the obtained ACFs can be class
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::f80524682daba2c28f274b5ba16477d2
https://doi.org/10.1007/s42452-020-3165-6
https://doi.org/10.1007/s42452-020-3165-6
Publikováno v:
ISRN Artificial Intelligence. 2013:1-17
We introduce a new model for describing word frequency distributions in documents for automatic text classification tasks. In the model, the gamma-Poisson probability distribution is used to achieve better text modeling. The framework of the modeling
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8f6911bb49c59ea3522439c3b5d4bfcb
https://doi.org/10.1155/2013/829630
https://doi.org/10.1155/2013/829630
Autor:
Yoshindo Kida, Masaki Ishii, Hiromi Amano, Saori Hashimoto, Katsuji Ikekubo, Yuriko Kurahashi, Kaoru Takahashi, Tsutomu Kamino, Toshikazu Nishio, Kanako Ika
Publikováno v:
Health Evaluation and Promotion. 40:468-475
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b3b7e4b78c7004dc9edbe514e6a76b47
https://doi.org/10.7143/jhep.40.468
https://doi.org/10.7143/jhep.40.468
Publikováno v:
Expert Systems with Applications. 38:4978-4989
Research highlights? Feature selections using Type-I metrics ( ? P 2 and Gini index) achieve the comparable classification performances with those of the combination framework using Type-III metrics (signed ?2 and signed information gain). ? The perf
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::27bd2024089258b77299cf9694299778
https://doi.org/10.1016/j.eswa.2010.09.153
https://doi.org/10.1016/j.eswa.2010.09.153
Publikováno v:
Expert Systems with Applications. 37:2273-2281
In the previous paper (Ogura, H., Amano, H., & Kondo, M. (2009). Feature selection with a measure of deviations from Poisson in text categorization. Expert Systems with Applications, 36, 6826-6832.), we proposed a new metric, @g"P^2, for selecting fe
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::5c18ba7f4c4cb85a3d3c08fc48106b8f
https://doi.org/10.1016/j.eswa.2009.07.045
https://doi.org/10.1016/j.eswa.2009.07.045
Publikováno v:
Expert Systems with Applications. 36:6826-6832
To improve the performance of automatic text classification, it is desirable to reduce a high dimensionality of the feature space. In this paper, we propose a new measure for selecting features, which estimates term importance based on how largely th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d69ae345cad58d861161d1c75aadb33c
https://doi.org/10.1016/j.eswa.2008.08.006
https://doi.org/10.1016/j.eswa.2008.08.006