A distributed high efficiency similarity matrix computation method based on users’ mobile network access location
A distributed similarity matrix computation method based on users’ mobile network access location was proposed.MapReduce computing framework in the Hadoop ecosystem was used,and users’ mobile network access location information was considered as prior knowledge,then users were divided based on geogr...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2018-05-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018136/ |
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| Summary: | A distributed similarity matrix computation method based on users’ mobile network access location was proposed.MapReduce computing framework in the Hadoop ecosystem was used,and users’ mobile network access location information was considered as prior knowledge,then users were divided based on geographic location information and the similarity calculation was performed.The experimental results show that the computational efficiency of the proposed method is increased by nearly 25 times compared with the existing similarity matrix computation method.As for the outcome of the community detection,the proposed method get nearly the same results as the existing similar matrix computation method,the agreement rate is nearly 99.9%. |
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| ISSN: | 1000-0801 |