Application of improved multi-model fusion technology in customer service answering system
With the development of artificial intelligence(AI),more and more companies use machine customer service instead of manual customer service.However,if the traditional keyword model is adopted,the accuracy of the machine customer service is difficult to improve.If the deep learning model is used,the...
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| Format: | Article |
| Language: | zho |
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Beijing Xintong Media Co., Ltd
2018-12-01
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| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018308/ |
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| _version_ | 1841530443238735872 |
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| author | Guangmin WANG Yaofeng WANG |
| author_facet | Guangmin WANG Yaofeng WANG |
| author_sort | Guangmin WANG |
| collection | DOAJ |
| description | With the development of artificial intelligence(AI),more and more companies use machine customer service instead of manual customer service.However,if the traditional keyword model is adopted,the accuracy of the machine customer service is difficult to improve.If the deep learning model is used,the predict result is poor when the user problem is short text.Aiming at these problems,an algorithm combining keyword model and deep learning model based on word vector was proposed.The training and prediction of the model was realized,and the advantages were shown in the comparison with the accuracy of the traditional algorithm. |
| format | Article |
| id | doaj-art-547666f54a2e4f6799e2715fc06fb6ff |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2018-12-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-547666f54a2e4f6799e2715fc06fb6ff2025-01-15T03:03:39ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012018-12-013411011659592532Application of improved multi-model fusion technology in customer service answering systemGuangmin WANGYaofeng WANGWith the development of artificial intelligence(AI),more and more companies use machine customer service instead of manual customer service.However,if the traditional keyword model is adopted,the accuracy of the machine customer service is difficult to improve.If the deep learning model is used,the predict result is poor when the user problem is short text.Aiming at these problems,an algorithm combining keyword model and deep learning model based on word vector was proposed.The training and prediction of the model was realized,and the advantages were shown in the comparison with the accuracy of the traditional algorithm.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018308/question and answer systemdeep learningAI |
| spellingShingle | Guangmin WANG Yaofeng WANG Application of improved multi-model fusion technology in customer service answering system Dianxin kexue question and answer system deep learning AI |
| title | Application of improved multi-model fusion technology in customer service answering system |
| title_full | Application of improved multi-model fusion technology in customer service answering system |
| title_fullStr | Application of improved multi-model fusion technology in customer service answering system |
| title_full_unstemmed | Application of improved multi-model fusion technology in customer service answering system |
| title_short | Application of improved multi-model fusion technology in customer service answering system |
| title_sort | application of improved multi model fusion technology in customer service answering system |
| topic | question and answer system deep learning AI |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2018308/ |
| work_keys_str_mv | AT guangminwang applicationofimprovedmultimodelfusiontechnologyincustomerserviceansweringsystem AT yaofengwang applicationofimprovedmultimodelfusiontechnologyincustomerserviceansweringsystem |