Boosting MBR based kNN Search over Multimedia Data by Approximate Pruning Metric
Shuguo Yang, Chunxia Li
Available Online November 2012.
- https://doi.org/10.2991/citcs.2012.73How to use a DOI?
- MBR; kNN search; Multimedia indexing; Multidimensional pruning
- MBR (Minimum Bounding Rectangle) has been widely used to represent multimedia data objects in R*-Tree family indexing techniques. In this paper, in order to improve the performance of kNN searching over multimedia data, we propose an approach to reduce the computation cost of MINMAXDIST by using its approximate upper bound instead of its precise value, and then we use it to construct two stronger heuristics for kNN pruning, which are helpful to avoid visiting unnecessary data objects and MBRs. The experimental results show that the proposed approach can reduce the computation cost and boost the overall performance in R*-Tree based kNN searching tasks.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Shuguo Yang AU - Chunxia Li PY - 2012/11 DA - 2012/11 TI - Boosting MBR based kNN Search over Multimedia Data by Approximate Pruning Metric BT - 2012 National Conference on Information Technology and Computer Science PB - Atlantis Press SP - 276 EP - 279 SN - 1951-6851 UR - https://doi.org/10.2991/citcs.2012.73 DO - https://doi.org/10.2991/citcs.2012.73 ID - Yang2012/11 ER -