Invention Grant
- Patent Title: High-dimensional data nearest-neighbor query method based on variable-length hash codes
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Application No.: US16671181Application Date: 2019-11-01
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Publication No.: US11488061B2Publication Date: 2022-11-01
- Inventor: Jiangbo Qian , Yanduo Ren , Yao Sun , Wei Hu
- Applicant: Ningbo University
- Applicant Address: CN Zhejiang
- Assignee: Ningbo University
- Current Assignee: Ningbo University
- Current Assignee Address: CN Zhejiang
- Agency: JCIPRNET
- Priority: CN201811298578.4 20181102
- Main IPC: G06F15/16
- IPC: G06F15/16 ; G06N20/00 ; G06F16/2455 ; G06F17/14 ; G06F16/22

Abstract:
A high-dimensional data nearest-neighbor query method based on variable-length hash codes is disclosed. Specifically, in this method, hash codes with the same code frequency are taken as a sub-data set, all the sub-data sets are ranked, a compression ratio is set for each sub-data set, the sub-data sets are compressed and trained according to the compression ratios, and hash codes and original codes corresponding to the trained sub-data sets are obtained; the hash code of each trained sub-data sets is copied to obtain multiple replicas, and the original codes and the corresponding replicas are strung to obtain strung hash codes which are integrated to form a final nearest-neighbor query table; and, a query code is obtained, and the nearest-neighbor query table is searched for a nearest-neighbor data set to complete query. The query efficiency and accuracy are greatly improved according to the invention.
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