Exquisitor at the Lifelog Search Challenge 2019

O. Khan, Björn þór Jónsson, Jan Zahálka, S. Rudinac, M. Worring
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引用次数: 16

Abstract

Interactive learning is an umbrella term for methods that attempt to understand the information need of the user and formulate queries that satisfy that information need. We propose to apply the state of the art in interactive multimodal learning to visual lifelog exploration and search, using the Exquisitor system. Exquisitor is a highly scalable interactive learning system, which uses semantic features extracted from visual content and text to suggest relevant media items to the user, based on user relevance feedback on previously suggested items. Findings from our initial experiments indicate that interactive multimodal learning will likely work well for some LSC tasks, but also suggest some potential enhancements.
2019年生活日志搜索挑战赛的设计师
交互式学习是试图理解用户的信息需求并制定满足该信息需求的查询的方法的总称。我们建议使用Exquisitor系统,将交互式多模式学习的最新技术应用于视觉生活日志的探索和搜索。Exquisitor是一个高度可扩展的交互式学习系统,它使用从视觉内容和文本中提取的语义特征,根据用户对先前建议项目的相关性反馈,向用户推荐相关的媒体项目。我们最初的实验结果表明,交互式多模式学习可能对一些LSC任务有效,但也表明了一些潜在的增强。
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