AdaIndex: An Adaptive Index Structure for Fast Similarity Search in Metric Spaces

Authors:
Tao Ban;Shanqing Guo;Qiuliang Xu;Youki Kadobayashi
Affiliations:
National Institute of Information and Communications Technology, Tokyo, Japan 184-8795;School of Computer Science and Technology, Shandong University, Jinan, China;School of Computer Science and Technology, Shandong University, Jinan, China;National Institute of Information and Communications Technology, Tokyo, Japan 184-8795
Venue:
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Year:
2009

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Abstract

The Distance Index (D-index) is a recently introduced metric indexing structure which has state-of-the-art performance in large scale metric search applications. Inspired by D-index, we introduce a novel index structure, termed AdaIndex, for fast similarity search in generic metric spaces. With multiple principles from other advanced algorithms, AdaIndex shows a significant improvement in reduction of distance calculations compared with D-index. To treat with application with different system limitations and diverse nature of data, we introduce a parameter tuning algorithm to build an optimal AdaIndex structure with minimal overall computational costs. The efficiency of AdaIndex is validated on a series of simulation experiments.