基于语义特征的互联网数据挖掘目标识别

Jing Xu, S. Okada, K. Nitta
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引用次数: 0

摘要

我们考虑了一个自动对象描述和聚类问题。针对传统基于图像处理的目标识别算法只能在图像库中对目标进行聚类的问题,本文提出了一种用人类语言描述目标,并以文本处理的方式将相似的目标分组在一起的方法。本文描述了一种通过打印在物体本身或其包装箱表面的文本标签来识别物体的系统。通过对它们的分析,可以用英语单词来描述对象,然后聚类到相应的组中。
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Semantic-Feature-Based Object Recognition by Using Internet Data Mining
We consider a problem of automated object description and clustering. Because traditional image-processing-based object recognition algorithms can only cluster objects in image-base, we propose a method to describe an object in human language and group similar objects together in text-processing way. This paper describes a system that recognizes objects with text labels printed on the surface of objects themselves or their packing cases. By analyzing them, objects could be described in English words, and then be clustered into corresponding groups.
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