Deep factorization machine model based on attention capsule
Aiming at the problems of single feature combination of recommendation model, resolution of a large amount of valuable feature information, and over-fitting in deep learning, a new attentional scoring mechanism called attention capsule was designed, and a deep factorization machine model based on at...
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| Format: | Article |
| Language: | zho |
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Editorial Department of Journal on Communications
2021-10-01
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| Series: | Tongxin xuebao |
| Subjects: | |
| Online Access: | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021185/ |
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| _version_ | 1841539251810861056 |
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| author | Yiran GU Zhupeng YAO Haigen YANG |
| author_facet | Yiran GU Zhupeng YAO Haigen YANG |
| author_sort | Yiran GU |
| collection | DOAJ |
| description | Aiming at the problems of single feature combination of recommendation model, resolution of a large amount of valuable feature information, and over-fitting in deep learning, a new attentional scoring mechanism called attention capsule was designed, and a deep factorization machine model based on attention capsule was proposed.Users’ historical clicking and candidate items were processed through weight calculation based on the DeepFM model, reducing the impact of irrelevant features on the model, and the differential impact of different historical behaviors on users’ interests was fully explored.The adaptive regularization formulation was added to the training, which effectively reduced over-fitting without affecting the training speed.The comparison test on two public data sets shows that the proposed model is significantly enhanced in loss function and GAUC compared to other models. |
| format | Article |
| id | doaj-art-eda181e46854400a92a693a80d0df419 |
| institution | Kabale University |
| issn | 1000-436X |
| language | zho |
| publishDate | 2021-10-01 |
| publisher | Editorial Department of Journal on Communications |
| record_format | Article |
| series | Tongxin xuebao |
| spelling | doaj-art-eda181e46854400a92a693a80d0df4192025-01-14T07:22:57ZzhoEditorial Department of Journal on CommunicationsTongxin xuebao1000-436X2021-10-014213013959745449Deep factorization machine model based on attention capsuleYiran GUZhupeng YAOHaigen YANGAiming at the problems of single feature combination of recommendation model, resolution of a large amount of valuable feature information, and over-fitting in deep learning, a new attentional scoring mechanism called attention capsule was designed, and a deep factorization machine model based on attention capsule was proposed.Users’ historical clicking and candidate items were processed through weight calculation based on the DeepFM model, reducing the impact of irrelevant features on the model, and the differential impact of different historical behaviors on users’ interests was fully explored.The adaptive regularization formulation was added to the training, which effectively reduced over-fitting without affecting the training speed.The comparison test on two public data sets shows that the proposed model is significantly enhanced in loss function and GAUC compared to other models.http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021185/recommendation modeldeep learningattention capsulefactorization machineadaptive regularization |
| spellingShingle | Yiran GU Zhupeng YAO Haigen YANG Deep factorization machine model based on attention capsule Tongxin xuebao recommendation model deep learning attention capsule factorization machine adaptive regularization |
| title | Deep factorization machine model based on attention capsule |
| title_full | Deep factorization machine model based on attention capsule |
| title_fullStr | Deep factorization machine model based on attention capsule |
| title_full_unstemmed | Deep factorization machine model based on attention capsule |
| title_short | Deep factorization machine model based on attention capsule |
| title_sort | deep factorization machine model based on attention capsule |
| topic | recommendation model deep learning attention capsule factorization machine adaptive regularization |
| url | http://www.joconline.com.cn/zh/article/doi/10.11959/j.issn.1000-436x.2021185/ |
| work_keys_str_mv | AT yirangu deepfactorizationmachinemodelbasedonattentioncapsule AT zhupengyao deepfactorizationmachinemodelbasedonattentioncapsule AT haigenyang deepfactorizationmachinemodelbasedonattentioncapsule |