EFH:an online unsupervised hash learning algorithm
Many unsupervised learning to hash algorithm needs to load all data to memory in the training phase,which will occupy a large memory space and cannot be applied to streaming data.An unsupervised online learning to hash algorithm called evolutionary forest hash (EFH) was proposed.In a large-scale dat...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2020-03-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020055/ |
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| author | Zhenyu SHOU Jiangbo QIAN Yihong DONG Huahui CHEN |
| author_facet | Zhenyu SHOU Jiangbo QIAN Yihong DONG Huahui CHEN |
| author_sort | Zhenyu SHOU |
| collection | DOAJ |
| description | Many unsupervised learning to hash algorithm needs to load all data to memory in the training phase,which will occupy a large memory space and cannot be applied to streaming data.An unsupervised online learning to hash algorithm called evolutionary forest hash (EFH) was proposed.In a large-scale data retrieval scenario,the improved evolution tree can be used to learn the spatial topology of the data.A path coding strategy was proposed to map leaf nodes to similarity-preserved binary code.To further improve the querying performance,ensemble learning was combined,and an online evolving forest hashing method was proposed based on the evolving trees.Finally,the feasibility of this method was proved by experiments on two widely used data sets. |
| format | Article |
| id | doaj-art-7bed6a750f694240ab7a3bf8993bd9e8 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2020-03-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-7bed6a750f694240ab7a3bf8993bd9e82025-01-15T03:01:00ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012020-03-0136718259584093EFH:an online unsupervised hash learning algorithmZhenyu SHOUJiangbo QIANYihong DONGHuahui CHENMany unsupervised learning to hash algorithm needs to load all data to memory in the training phase,which will occupy a large memory space and cannot be applied to streaming data.An unsupervised online learning to hash algorithm called evolutionary forest hash (EFH) was proposed.In a large-scale data retrieval scenario,the improved evolution tree can be used to learn the spatial topology of the data.A path coding strategy was proposed to map leaf nodes to similarity-preserved binary code.To further improve the querying performance,ensemble learning was combined,and an online evolving forest hashing method was proposed based on the evolving trees.Finally,the feasibility of this method was proved by experiments on two widely used data sets.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020055/nearest neighbor queryevolving treeonlinehash learningensemble learning |
| spellingShingle | Zhenyu SHOU Jiangbo QIAN Yihong DONG Huahui CHEN EFH:an online unsupervised hash learning algorithm Dianxin kexue nearest neighbor query evolving tree online hash learning ensemble learning |
| title | EFH:an online unsupervised hash learning algorithm |
| title_full | EFH:an online unsupervised hash learning algorithm |
| title_fullStr | EFH:an online unsupervised hash learning algorithm |
| title_full_unstemmed | EFH:an online unsupervised hash learning algorithm |
| title_short | EFH:an online unsupervised hash learning algorithm |
| title_sort | efh an online unsupervised hash learning algorithm |
| topic | nearest neighbor query evolving tree online hash learning ensemble learning |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2020055/ |
| work_keys_str_mv | AT zhenyushou efhanonlineunsupervisedhashlearningalgorithm AT jiangboqian efhanonlineunsupervisedhashlearningalgorithm AT yihongdong efhanonlineunsupervisedhashlearningalgorithm AT huahuichen efhanonlineunsupervisedhashlearningalgorithm |