Fusion of auto encoders and multi-modal data based video recommendation method
Nowadays, the commonly used linear structure video recommendation methods have the problems of non-personalized recommendation results and low accuracy, so it is extremely urgent to develop high-precision personalized video recommendation method.A video recommendation method based on the fusion of a...
Saved in:
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Beijing Xintong Media Co., Ltd
2021-02-01
|
| Series: | Dianxin kexue |
| Subjects: | |
| Online Access: | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021031/ |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1841529099908022272 |
|---|---|
| author | Qiuyang GU Chunhua JU Gongxing WU |
| author_facet | Qiuyang GU Chunhua JU Gongxing WU |
| author_sort | Qiuyang GU |
| collection | DOAJ |
| description | Nowadays, the commonly used linear structure video recommendation methods have the problems of non-personalized recommendation results and low accuracy, so it is extremely urgent to develop high-precision personalized video recommendation method.A video recommendation method based on the fusion of autoencoders and multi-modal data was presented.This method fused two data including text and vision for video recommendation.To be specific, the method proposed firstly used bag of words and TF-IDF methods to describe text data, and then fused the obtained features with deep convolutional descriptors extracted from visual data, so that each video document could get a multi-modal descriptors, and constructed low-dimensional sparse representation by autoencoders.Experiments were performed on the proposed model by using three real data sets.The result shows that compared with the single-modal recommendation method, the recommendation results of the proposed method are significantly improved, and the performance is better than the reference method. |
| format | Article |
| id | doaj-art-79de5e71d4de49849ceedc2608d2ac0b |
| institution | Kabale University |
| issn | 1000-0801 |
| language | zho |
| publishDate | 2021-02-01 |
| publisher | Beijing Xintong Media Co., Ltd |
| record_format | Article |
| series | Dianxin kexue |
| spelling | doaj-art-79de5e71d4de49849ceedc2608d2ac0b2025-01-15T03:25:51ZzhoBeijing Xintong Media Co., LtdDianxin kexue1000-08012021-02-0137829859806784Fusion of auto encoders and multi-modal data based video recommendation methodQiuyang GUChunhua JUGongxing WUNowadays, the commonly used linear structure video recommendation methods have the problems of non-personalized recommendation results and low accuracy, so it is extremely urgent to develop high-precision personalized video recommendation method.A video recommendation method based on the fusion of autoencoders and multi-modal data was presented.This method fused two data including text and vision for video recommendation.To be specific, the method proposed firstly used bag of words and TF-IDF methods to describe text data, and then fused the obtained features with deep convolutional descriptors extracted from visual data, so that each video document could get a multi-modal descriptors, and constructed low-dimensional sparse representation by autoencoders.Experiments were performed on the proposed model by using three real data sets.The result shows that compared with the single-modal recommendation method, the recommendation results of the proposed method are significantly improved, and the performance is better than the reference method.http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021031/autoencodermulti-modal representationdata fusionvideo recommendation |
| spellingShingle | Qiuyang GU Chunhua JU Gongxing WU Fusion of auto encoders and multi-modal data based video recommendation method Dianxin kexue autoencoder multi-modal representation data fusion video recommendation |
| title | Fusion of auto encoders and multi-modal data based video recommendation method |
| title_full | Fusion of auto encoders and multi-modal data based video recommendation method |
| title_fullStr | Fusion of auto encoders and multi-modal data based video recommendation method |
| title_full_unstemmed | Fusion of auto encoders and multi-modal data based video recommendation method |
| title_short | Fusion of auto encoders and multi-modal data based video recommendation method |
| title_sort | fusion of auto encoders and multi modal data based video recommendation method |
| topic | autoencoder multi-modal representation data fusion video recommendation |
| url | http://www.telecomsci.com/zh/article/doi/10.11959/j.issn.1000-0801.2021031/ |
| work_keys_str_mv | AT qiuyanggu fusionofautoencodersandmultimodaldatabasedvideorecommendationmethod AT chunhuaju fusionofautoencodersandmultimodaldatabasedvideorecommendationmethod AT gongxingwu fusionofautoencodersandmultimodaldatabasedvideorecommendationmethod |