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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| Main Authors: | , |
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| Format: | Article |
| Language: | zho |
| Published: |
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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| Summary: | 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. |
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| ISSN: | 1000-0801 |