Theme-related keyword extraction from free text descriptions of image contents for tagging

Joonmyun Cho, Yoon-Seop Chang, Sung-Ho Lee
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Abstract

This paper discusses a method for automatic theme-related keyword extraction from users' natural language comments on their photographs and videos. ‘Theme’ indicates the concepts circumscribing and describing the content of the photos and videos such as pets, natural sites, palaces and places. The method employs a deep learning algorithm, RNN(Recurrent Neural Network) that is good at recognizing implicit patterns of sequential data. The method has been applied to the construction of a place-related image content DB, and delivers reasonably good performance even in case the measure (i.e. themes of image contents) is abstract and vague.
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从图像内容的自由文本描述中提取主题相关关键字进行标记
本文讨论了一种从用户对照片和视频的自然语言评论中自动提取主题相关关键词的方法。“主题”是指限定和描述照片和视频内容的概念,如宠物、自然景观、宫殿和地方。该方法采用深度学习算法RNN(递归神经网络),擅长识别序列数据的隐式模式。该方法已应用于构建与地点相关的图像内容数据库,即使度量(即图像内容的主题)是抽象和模糊的,也能提供相当好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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