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网页对象分类的社会标记图研究

Exploring Social Tagging Graph for Web Object Classification
课程网址: http://videolectures.net/kdd09_yin_estgwoc/  
主讲教师: Zhijun Yin
开课单位: 伊利诺伊大学
开课时间: 2009-09-14
课程语种: 英语
中文简介:
本文通过对社会标签的新探索,研究了Web对象分类问题。自动将Web对象分类为可管理的语义类别长期以来一直是索引,浏览,搜索和挖掘这些对象的基本预处理过程。异构Web对象(尤其是非文本对象,如产品,图片和视频)的爆炸性增长使得Web分类问题变得越来越具有挑战性。这些对象经常缺乏易于提取的特征,包括语义信息,彼此之间的相互关联,以及具有类别标签的训练示例。在本文中,我们探索社会标记数据来弥补这一差距。我们将Web对象分类问题作为对象和标记图形上的优化问题进行转换。然后,我们提出了一种有效的算法,该算法不仅利用社交标签作为对象的丰富语义特征,而且还通过社交标签的隐式连接推断来自同构和异构标记对象的未标记对象的类别。实验结果表明,社交标签的探索有效地促进了Web对象的分类。我们的算法明显优于一般分类方法的技术水平。
课程简介: This paper studies web object classification problem with the novel exploration of social tags. Automatically classifying web objects into manageable semantic categories has long been a fundamental preprocess for indexing, browsing, searching, and mining these objects. The explosive growth of heterogeneous web objects, especially non-textual objects such as products, pictures, and videos, has made the problem of web classification increasingly challenging. Such objects often suffer from a lack of easy-extractable features with semantic information, interconnections between each other, as well as training examples with category labels. In this paper, we explore the social tagging data to bridge this gap. We cast web object classification problem as an optimization problem on a graph of objects and tags. We then propose an efficient algorithm which not only utilizes social tags as enriched semantic features for the objects, but also infers the categories of unlabeled objects from both homogeneous and heterogeneous labeled objects, through the implicit connection of social tags. Experiment results show that the exploration of social tags effectively boosts web object classification. Our algorithm significantly outperforms the state-of-the-art of general classification methods.
关 键 词: 社会标签; 对象分类; 语义类别
课程来源: 视频讲座网
最后编审: 2020-06-12:章泽平(课程编辑志愿者)
阅读次数: 37