文章基本信息

标题：新聞記事のアクセスログを用いたユーザ属性の逐次推定
本地全文：下载
作者：工藤航 ; 鳥海不二夫
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2019
卷号：34
期号：5
页码：1-9
DOI：10.1527/tjsai.wd-E
出版社：The Japanese Society for Artificial Intelligence
摘要：With the spread of social media and e-commerce websites, the technology of user profiling from users’ action history has attracted a lot of interest. Users’ action history can be acquired both in the passive way and in the active (interactive) way, and previous studies have found out how to presume the users’ profile from their action history which is acquired passively. The purpose of this study was to find out the best way to interact with users for efficient user profiling. First, we constructed a CNN (Convolutional Neural Network) model which presumes user’s profile. Next, we proposed three ways to interact with users for efficient user profiling and compared them. Consequently, two ways of the three were discovered to be effective to streamline the user profiling. And we provided some analyses of the ways, which revealed that the CNN model’s output for an item could be utilized for efficient user profiling , and considering the probability that each item is consumed by the target user could provide more efficient ways.
关键词：convolutional neural network;user profiling;efficiency