An AkNN Algorithm for High-Dimensional Big Data
A new variant of k nearest neighbor queries，which called as all k-nearest neighbor queries（AkNN），is a process to search the k nearest neighbors of each object in a data set.An AkNN query algorithm for high-dimensional big data on the Hadoop system was proposed.Using the banding technique and the p-s...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2015-07-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2015171/ |
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| Summary: | A new variant of k nearest neighbor queries，which called as all k-nearest neighbor queries（AkNN），is a process to search the k nearest neighbors of each object in a data set.An AkNN query algorithm for high-dimensional big data on the Hadoop system was proposed.Using the banding technique and the p-stable LSH algorithm，dimensionality reduction was performed，then the data was embeded in a Z-order curve.The preprocessed data were continued to be treated on a MapReduce framework in a distributed parallel manner.Experimental results show that the proposed algorithm can efficiently handle AkNN queries for large-scale high-dimensional data. |
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| ISSN: | 1000-0801 |