@techreport{oai:ipsj.ixsq.nii.ac.jp:00232602,
 author = {林, 芳樹 and 千葉, 昭宏 and 外山, 篤史 and 塩田, 哲哉 and 谷口, 裕紀 and 浅井, 洋樹 and 韓, 琳 and 小林, 拓也 and 山田, 仰 and 石倉, 岳 and 上田, 彩花 and 小西, 慧 and 倉沢, 央 and 富田, 準二 and 佐藤, 篤 and Yoshiki, Hayashi and Akihiro, Chiba and Atsushi, Toyama and Tetsuya, Shioda and Yuuki, Taniguchi and Hiroki, Asai and Rin, Kan and Takuya, Kobayashi and Aogu, Yamada and Gaku, Ishikura and Ayaka, Ueda and Satoshi, Konishi and Hisashi, Kurasawa and Junji, Tomita and Atsushi, Sato},
 issue = {42},
 month = {Feb},
 note = {企業は顧客一人ひとりに合わせたきめ細かなサポートを実現するため，属性や行動などの顧客情報からニーズや課題をとらえて，最適な方法で支援する必要がある．本稿では，顧客の将来行動を予測に加え，その行動実現を促すサポート情報の出力方式について提案する．また，出力した情報を LLM に与え，顧客応対に活用する方式を検討する．, To provide fine-tuned support tailored to each customer, companies need to understand needs and issues from customer information, such as attributes and behaviors, and offer assistance in the most appropriate manner. We propose a method to predict future customer behavior and output support information to realize such behavior, and a method of using LLM as an interface to utilize the output information for customer service.},
 title = {カスタマーサポートにおける時系列分析手法とLLMの活用に関する一考察},
 year = {2024}
}