User behavior pattern mining method based on multi-dimension and multi-granularity analysis in telecom networks
In order to better understand the behavior of users in telecom networks,it takes CDR (call detail record) data of large-scale telecom network as the research object.By using the mixed probability model and feature engineering method,the multi-dimension characteristics of the call time,call frequency...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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POSTS&TELECOM PRESS Co., LTD
2018-10-01
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| Series: | 网络与信息安全学报 |
| Subjects: | |
| Online Access: | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2018083 |
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| _version_ | 1841530180439375872 |
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| author | Xiaotao CHENG Lixin JI Ruiyang HUANG Hongtao YU Yizhuo YANG |
| author_facet | Xiaotao CHENG Lixin JI Ruiyang HUANG Hongtao YU Yizhuo YANG |
| author_sort | Xiaotao CHENG |
| collection | DOAJ |
| description | In order to better understand the behavior of users in telecom networks,it takes CDR (call detail record) data of large-scale telecom network as the research object.By using the mixed probability model and feature engineering method,the multi-dimension characteristics of the call time,call frequency and connections are analyzed from the perspective of user groups and individuals.It is further refined from different time granularities such as hour,day,and week to realize effective discovery of call behavior patterns for different user groups.The distribution characteristics of user behavior are modeled by mixed probability model,which solves the problem of describing the distribution characteristics such as user's call time and frequency.Based on the dataset of a regional telecom network,the performance of decision tree,naive Bayes and SVM classification algorithm are compared.It proves the validity and computational feasibility of the proposed method.The differences in communication behavior patterns of different groups are also compared by taking the service numbers like express,flight and bank as examples. |
| format | Article |
| id | doaj-art-f3a853c266b44efa84e96ff963e571b3 |
| institution | Kabale University |
| issn | 2096-109X |
| language | English |
| publishDate | 2018-10-01 |
| publisher | POSTS&TELECOM PRESS Co., LTD |
| record_format | Article |
| series | 网络与信息安全学报 |
| spelling | doaj-art-f3a853c266b44efa84e96ff963e571b32025-01-15T03:13:04ZengPOSTS&TELECOM PRESS Co., LTD网络与信息安全学报2096-109X2018-10-014395159554395User behavior pattern mining method based on multi-dimension and multi-granularity analysis in telecom networksXiaotao CHENGLixin JIRuiyang HUANGHongtao YUYizhuo YANGIn order to better understand the behavior of users in telecom networks,it takes CDR (call detail record) data of large-scale telecom network as the research object.By using the mixed probability model and feature engineering method,the multi-dimension characteristics of the call time,call frequency and connections are analyzed from the perspective of user groups and individuals.It is further refined from different time granularities such as hour,day,and week to realize effective discovery of call behavior patterns for different user groups.The distribution characteristics of user behavior are modeled by mixed probability model,which solves the problem of describing the distribution characteristics such as user's call time and frequency.Based on the dataset of a regional telecom network,the performance of decision tree,naive Bayes and SVM classification algorithm are compared.It proves the validity and computational feasibility of the proposed method.The differences in communication behavior patterns of different groups are also compared by taking the service numbers like express,flight and bank as examples.http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2018083telecom networkmulti-dimensionmulti-granularity,mixture-of-Gaussianbehavior pattern mining |
| spellingShingle | Xiaotao CHENG Lixin JI Ruiyang HUANG Hongtao YU Yizhuo YANG User behavior pattern mining method based on multi-dimension and multi-granularity analysis in telecom networks 网络与信息安全学报 telecom network multi-dimension multi-granularity, mixture-of-Gaussian behavior pattern mining |
| title | User behavior pattern mining method based on multi-dimension and multi-granularity analysis in telecom networks |
| title_full | User behavior pattern mining method based on multi-dimension and multi-granularity analysis in telecom networks |
| title_fullStr | User behavior pattern mining method based on multi-dimension and multi-granularity analysis in telecom networks |
| title_full_unstemmed | User behavior pattern mining method based on multi-dimension and multi-granularity analysis in telecom networks |
| title_short | User behavior pattern mining method based on multi-dimension and multi-granularity analysis in telecom networks |
| title_sort | user behavior pattern mining method based on multi dimension and multi granularity analysis in telecom networks |
| topic | telecom network multi-dimension multi-granularity, mixture-of-Gaussian behavior pattern mining |
| url | http://www.cjnis.com.cn/thesisDetails#10.11959/j.issn.2096-109x.2018083 |
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