CNNを用いたマイクロイベント告知画像のクリック数予測手法の提案

カテゴリ: 論文誌(論文単位)

グループ名: 【C】電子・情報・システム部門

発行日: 2024/09/01

タイトル(英語): Proposal of a CNN-based Method for Predicting the Number of Clicks on Micro-event Flyer Images

著者名: 井上　大地（(株) D2C），松本　慎平（広島工業大学）

著者名(英語): Daichi Inoue (D2C Inc.), Shimpei Matsumoto (Hiroshima Institute of Technology)

キーワード: ソーシャルメディア，告知画像，CNN，クリック数　　social media，flyer image，CNN，number of clicks

要約(英語): The web service “Tame-Map” enables users to easily transmit, view, and share information about small local activities, known as micro-events, which typically receive less attention on mainstream social media platforms. This study aims to develop a method for predicting the click rates of micro-event announcement images on “Tame-Map” and to evaluate the effectiveness of this approach. The research primarily utilizes machine learning techniques and constructs a predictive model employing Convolutional Neural Networks (CNN). The model assumes that thumbnail images of micro-events possess distinct features that attract viewers and utilizes these images as primary input data. Moreover, the study introduces an advanced model that incorporates meta-information, such as the event's location, as additional explanatory variables. The resulting model demonstrates adequate predictive accuracy, suggesting its potential as a standard method in future applications.

本誌: 電気学会論文誌C（電子・情報・システム部門誌） Vol.144 No.9 （2024） 特集：知能メカトロニクス分野と連携する知覚情報技術

本誌掲載ページ: 942-954 p

原稿種別: 論文／日本語

電子版へのリンク: https://www.jstage.jst.go.jp/article/ieejeiss/144/9/144_942/_article/-char/ja/