Telecom complaint hot topic detection method based on density peaks clustering
In view of the lack of effective detection methods for hot topics in telecom industry,a method of complaint hotspots detection based on density peaks clustering algorithm was proposed.Firstly,a special vocabulary for telecommunication industry was established to segment the complaint samples.The vec...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2019-05-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2019076/ |
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| _version_ | 1841530536997158912 |
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| author | Jun JIANG Hua HUANG Tiaojuan REN Denghui ZHANG |
| author_facet | Jun JIANG Hua HUANG Tiaojuan REN Denghui ZHANG |
| author_sort | Jun JIANG |
| collection | DOAJ |
| description | In view of the lack of effective detection methods for hot topics in telecom industry,a method of complaint hotspots detection based on density peaks clustering algorithm was proposed.Firstly,a special vocabulary for telecommunication industry was established to segment the complaint samples.The vector space model was used to represent the text segmentation.Then,the similarity and density of the text segmentation were calculated,and the clustering analysis of the words was carried out by using the density peaks clustering algorithm.Finally,keywords were selected and sorted by clustering.This method was applied to the complaint hotspots detection tasks within a telecom company.The results show that this method is effective and has practical application value. |
| format | Article |
| id | doaj-art-9fdd89918921420791865dce9809d947 |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2019-05-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-9fdd89918921420791865dce9809d9472025-01-15T03:02:56ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012019-05-01359710359589881Telecom complaint hot topic detection method based on density peaks clusteringJun JIANGHua HUANGTiaojuan RENDenghui ZHANGIn view of the lack of effective detection methods for hot topics in telecom industry,a method of complaint hotspots detection based on density peaks clustering algorithm was proposed.Firstly,a special vocabulary for telecommunication industry was established to segment the complaint samples.The vector space model was used to represent the text segmentation.Then,the similarity and density of the text segmentation were calculated,and the clustering analysis of the words was carried out by using the density peaks clustering algorithm.Finally,keywords were selected and sorted by clustering.This method was applied to the complaint hotspots detection tasks within a telecom company.The results show that this method is effective and has practical application value.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2019076/hot topic detectiontext segmentationcluster analysis |
| spellingShingle | Jun JIANG Hua HUANG Tiaojuan REN Denghui ZHANG Telecom complaint hot topic detection method based on density peaks clustering Dianxin kexue hot topic detection text segmentation cluster analysis |
| title | Telecom complaint hot topic detection method based on density peaks clustering |
| title_full | Telecom complaint hot topic detection method based on density peaks clustering |
| title_fullStr | Telecom complaint hot topic detection method based on density peaks clustering |
| title_full_unstemmed | Telecom complaint hot topic detection method based on density peaks clustering |
| title_short | Telecom complaint hot topic detection method based on density peaks clustering |
| title_sort | telecom complaint hot topic detection method based on density peaks clustering |
| topic | hot topic detection text segmentation cluster analysis |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2019076/ |
| work_keys_str_mv | AT junjiang telecomcomplainthottopicdetectionmethodbasedondensitypeaksclustering AT huahuang telecomcomplainthottopicdetectionmethodbasedondensitypeaksclustering AT tiaojuanren telecomcomplainthottopicdetectionmethodbasedondensitypeaksclustering AT denghuizhang telecomcomplainthottopicdetectionmethodbasedondensitypeaksclustering |