@inproceedings{6ac1bec7936c46b582db48b123e0f995,
title = "Construction of news article evaluation system using language generation model",
abstract = "This study constructed a news article evaluation system that utilizes a language generation model to analyze financial markets. This system enables us to analyze the effect of news articles distributed in financial markets on the stock price of a company. We added the generated news articles as data for analysis through GPT-2 and verified the accuracy of the constructed system. As a result of empirical analyses, we confirmed that the accuracy of the model with the generated news articles improved. More detailed analyses are planned for the future.",
keywords = "Deep learning, Financial markets, GPT-2, LSTM, Language generation, Natural language processing, News evaluation system",
author = "Yoshihiro Nishi and Aiko Suge and Hiroshi Takahashi",
note = "Publisher Copyright: {\textcopyright} The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2020.; 14th International KES Conference on Agents and Multi-Agent Systems: Technologies and Applications, KES-AMSTA 2020 ; Conference date: 17-06-2020 Through 19-07-2020",
year = "2020",
doi = "10.1007/978-981-15-5764-4_29",
language = "English",
isbn = "9789811557637",
series = "Smart Innovation, Systems and Technologies",
publisher = "Springer",
pages = "313--320",
editor = "G. Jezic and M. Kusek and J. Chen-Burger and R. Sperka and Howlett, {Robert J.} and Howlett, {Robert J.} and Jain, {Lakhmi C.} and Jain, {Lakhmi C.} and Jain, {Lakhmi C.}",
booktitle = "Agents and Multi-Agent Systems",
}