多视图主题模型学习,自动生成受众元数据

Wonjoo Park, Jeong-Woo Son, Sang-Yun Lee, Sun-Joong Kim
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引用次数: 0

摘要

本文提出了一种基于多视角主题模型学习的视频片段观众元数据自动生成方法。我们使用广播内容的封闭字幕、用户的订阅信息和观看历史。通过在没有用户数据的情况下基于字幕或脚本学习主题,现有的主题模型在用于用户目标服务方面存在局限性。为了克服这一局限性,本文提出了一种多视角主题模型学习技术,该技术使用了广播内容的封闭字幕和受众群体的收视率等多领域数据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Multi-view topic model learning to generate audience metadata automatically
In this paper, we propose a study on multi-view topic model learning to generate automatically audience metadata for clips. We use closed caption of broadcasting contents, user's subscription information and viewing history. An existing topic model has limits to being utilized for user targeted services by learning topics based on subtitles or scripts without user data. To overcome this limitation, this paper proposes a multi-view topic model learning technique using multi domain data such as closed caption of broadcast contents and viewing rating of audience groups.
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