Zobrazeno 1 - 4
of 4
pro vyhledávání: '"Seongik Park"'
Publikováno v:
SNPD
Language Modeling (LM) is a subtask in Natural Language Processing (NLP), and the goal of LM is to build a statistical language model that can learn and estimate a probability distribution of natural language over sentences of terms. Recently, many r
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::c0c9e338d1e613ed20234818846043ef
https://doi.org/10.1109/snpd.2018.8441130
https://doi.org/10.1109/snpd.2018.8441130
A Study on the Contribution Evaluation of Developer in Convergence Social App Manufacturing Platform
Publikováno v:
Journal of Digital Convergence. 13:225-233
The convergence social app manufacturing platform for both demander and developer in worldwide provides a collective collaborative development approach. This platform can bring enhanced productivity with exchange of views among participants. If the a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::305a4537772ac932878e239c21aa8a46
https://doi.org/10.14400/jdc.2015.13.9.225
https://doi.org/10.14400/jdc.2015.13.9.225
Publikováno v:
RACS
Sentiment analysis aims to observe and summarize a person's opinions or emotional states through textual data. Despite the demands of sentiment analysis methods for analyzing social media data, fundamental challenges still remained because user-gener
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b27577d6c35a5a8104e7d4344df1455f
https://doi.org/10.1145/3129676.3129702
https://doi.org/10.1145/3129676.3129702
Autor:
Yanggon Kim, Seongik Park
Publikováno v:
SERA
Sentiment classification categorizes people's opinions from the data. Nowadays, people express their personal interests, feelings, and opinions on social media, and the posts on social media are frequently used as the data for sentiment classificatio
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::030c57300a9e93c62d989850458b3001
https://doi.org/10.1109/sera.2016.7516126
https://doi.org/10.1109/sera.2016.7516126