myBUD中多媒体数据索引CFTree*的研究和实现

张  孝; 孙新云; 刘科研; 琚星星; 王  珊

myBUD中多媒体数据索引CFTree*的研究和实现

张孝^1,2,3,
孙新云^1,2,
刘科研⁴,
琚星星^1,2,
王珊^1,2

1(数据工程与知识工程教育部重点实验室(中国人民大学) 北京 100872) 2(中国人民大学信息学院北京 100872) 3(上海市智能信息处理重点实验室上海 200433) 4(诺基亚西门子通信中国研究院北京 100016) (zhangxiao@ruc.edu.cn)

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出版历程
- 发布日期: 2011-10-14

Research and Implementation of CFTree* Index on MultiMedia Data in myBUD

Zhang Xiao^1,2,3,
Sun Xinyun^1,2,
Liu Keyan⁴,
Ju Xingxing^1,2,
Wang Shan^1,2

1(Key Laboratory of Data Engineering and Knowledge Engineering (Renmin University of China), Ministry of Education, Beijing 100872) 2(School of Information, Renmin University of China, Beijing 100872) 3(Shanghai Key Laboratory of Intelligent Information Processing, Shanghai 200433) 4(Nokia-Siemens-Network Chief Technology Office Research, Beijing 100016)

摘要

摘要: 图片、音频、视频、网页等非结构化数据的高速增长使得如何高效管理它们成为一大挑战.提出的多媒体数据索引CFTree*是非结构化数据管理系统平台myBUD中对多媒体数据进行管理的具体研究和实现.CFTree*是基于簇特征树的层次树索引结构,可用于基于内容的近似kNN查询.实验表明,基于CFTree*索引结构的近似kNN查询性能比基于顺序扫描的kNN查询有60%左右的提高.与精确kNN相比,基于CFTree*索引的近似kNN查询结果与查询对象的平均相似度略低于精确kNN结果,但结果的多样性则优于精确kNN结果.
- 非结构化数据管理 /
- 聚类算法 /
- 扩展簇特征树 /
- 多媒体数据索引技术 /
- 近似kNN查询
Abstract: The ever-growing unstructure data, such as image, video, audio, web page, etc., bring the challenge of effective unstructured data management(USDM). In this work, CFTree* is proposed to index and manage the multimedia data in our USDM platform—myBUD. The CFTree* index is a hierarchical indexing structure built on the top of cluster feature tree. CFTree* can be leveraged in the approximate kNN query processing. The experimental result shows that the query performance of approximate kNN query based on CFTree* gains about 60% improvement over thaton sequence scan. The approximate kNN query result has lower average precision than exact kNN query result, but it has more diversity.
- unstructured data management(USDM) /
- clustering /
- CFTree* /
- multimedia index /
- approximate kNN query