Journal of Computer Applications ›› 2023, Vol. 43 ›› Issue (11): 3443-3448.DOI: 10.11772/j.issn.1001-9081.2022101628
• Artificial intelligence • Previous Articles Next Articles
Chuyuan WEI1(), Mengke WANG2, Chuanhao HU2, Guangqi ZHANG2
Received:
2022-10-31
Revised:
2023-03-17
Accepted:
2023-04-04
Online:
2023-05-24
Published:
2023-11-10
Contact:
Chuyuan WEI
About author:
WEI Chuyuan, born in 1977, Ph. D., associate professor. His research interests include natural language processing, data mining.Supported by:
通讯作者:
魏楚元
作者简介:
魏楚元(1977—),男,湖北武汉人,副教授,博士,CCF高级会员,主要研究方向:自然语言处理、数据挖掘 weichuyuan@bucea.edu.cn基金资助:
CLC Number:
Chuyuan WEI, Mengke WANG, Chuanhao HU, Guangqi ZHANG. Deep review attention neural network model for enhancing explainability of recommendation system[J]. Journal of Computer Applications, 2023, 43(11): 3443-3448.
魏楚元, 王梦珂, 户传豪, 张桄齐. 增强推荐系统可解释性的深度评论注意力神经网络模型[J]. 《计算机应用》唯一官方网站, 2023, 43(11): 3443-3448.
Add to citation manager EndNote|Ris|BibTeX
URL: http://www.joca.cn/EN/10.11772/j.issn.1001-9081.2022101628
数据集 | 用户数 | 项目数 | 评论交互数 |
---|---|---|---|
M-I | 1 429 | 900 | 10 261 |
Patio | 1 686 | 962 | 13 254 |
Automotive | 2 928 | 1 835 | 20 441 |
Beauty | 22 362 | 12 101 | 198 502 |
Tab. 1 Information of datasets
数据集 | 用户数 | 项目数 | 评论交互数 |
---|---|---|---|
M-I | 1 429 | 900 | 10 261 |
Patio | 1 686 | 962 | 13 254 |
Automotive | 2 928 | 1 835 | 20 441 |
Beauty | 22 362 | 12 101 | 198 502 |
模型 | M-I | Automotive | Patio | Beauty |
---|---|---|---|---|
PMF | 1.135 4 | 1.146 8 | 1.250 1 | 1.247 6 |
SVD++ | 1.019 6 | 0.962 1 | 1.102 4 | 1.135 2 |
DeepCF | 1.009 7 | 0.986 2 | 1.081 8 | 1.118 8 |
DeepCoNN | 1.028 6 | 0.933 3 | 1.043 2 | 1.126 9 |
TEM | 0.984 0 | 0.907 6 | 1.013 4 | 1.120 3 |
DER | 0.973 0 | 0.906 7 | 1.003 8 | 1.119 7 |
DRANN | 0.947 1 | 0.902 1 | 1.003 7 | 1.112 4 |
Tab. 2 RMSE comparison of different models on Amazon dataset
模型 | M-I | Automotive | Patio | Beauty |
---|---|---|---|---|
PMF | 1.135 4 | 1.146 8 | 1.250 1 | 1.247 6 |
SVD++ | 1.019 6 | 0.962 1 | 1.102 4 | 1.135 2 |
DeepCF | 1.009 7 | 0.986 2 | 1.081 8 | 1.118 8 |
DeepCoNN | 1.028 6 | 0.933 3 | 1.043 2 | 1.126 9 |
TEM | 0.984 0 | 0.907 6 | 1.013 4 | 1.120 3 |
DER | 0.973 0 | 0.906 7 | 1.003 8 | 1.119 7 |
DRANN | 0.947 1 | 0.902 1 | 1.003 7 | 1.112 4 |
数据集 | RMSE | |
---|---|---|
未添加编码器 | 添加编码器 | |
Patio | 1.320 0 | 1.003 7 |
Beauty | 1.257 2 | 1.112 4 |
M-I | 1.032 0 | 0.971 2 |
Tab. 3 Influence of deep encoder on RMSE of model
数据集 | RMSE | |
---|---|---|
未添加编码器 | 添加编码器 | |
Patio | 1.320 0 | 1.003 7 |
Beauty | 1.257 2 | 1.112 4 |
M-I | 1.032 0 | 0.971 2 |
1 | 于蒙, 何文涛, 周绪川, 等. 推荐系统综述[J]. 计算机应用, 2022, 42( 6): 1898- 1913. |
YU M, HE W T, ZHOU X C, et al. Review of recommender system [J]. Journal of Computer Applications, 2022, 42( 6): 1898- 1913. | |
2 | MU R H. A survey of recommender systems based on deep learning[J]. IEEE Access, 2018, 6: 69009- 69022. 10.1109/access.2018.2880197 |
3 | 田添星. 评论情感分析增强的深度推荐模型[J]. 计算机应用与软件, 2022, 39( 8): 258- 264. 10.3969/j.issn.1000-386x.2022.08.038 |
TIAN T X. Comment sentiment analysis enhanced deep recommendation model [J]. Computer Applications and Software, 2022, 39( 8): 258- 264. 10.3969/j.issn.1000-386x.2022.08.038 | |
4 | BOZANTA A, KUTLU B. HybRecSys: content-based contextual hybrid venue recommender system[J]. Journal of Information Science, 2019, 45( 2): 212- 226. 10.1177/0165551518786678 |
5 | LI X F, LI D. An improved collaborative filtering recommendation algorithm and recommendation strategy[J]. Mobile Information Systems, 2019, 2019( 13): No. 3560968. 10.1155/2019/3560968 |
6 | CENA F, CONSOLE L, VERNERO F. Logical foundations of knowledge-based recommender systems: a unifying spectrum of alternatives[J]. Information Sciences, 2021, 546( 1): 60- 73. 10.1016/j.ins.2020.07.075 |
7 | YOO H, CHUNG K. Deep learning-based evolutionary recommendation model for heterogeneous big data integration[J]. KSII Transactions on Internet and Information Systems, 2020, 14( 9): 3730- 3744. 10.3837/tiis.2020.09.009 |
8 | YU H T, GAO R B, WANG K, et al. A novel robust recommendation method based on kernel matrix factorization[J]. Journal of Intelligent & Fuzzy Systems, 2017, 32( 3): 2101- 2109. 10.3233/jifs-161705 |
9 | 田震, 潘腊梅, 王睿, 等. 深度矩阵分解推荐算法[J]. 软件学报, 2021, 32( 12): 3917- 3928. |
TIAN Z, PAN L M, WANG R, et al. Deep matrix factorization recommendation algorithm [J]. Journal of Software, 2020. 32 ( 12): 3917- 3928. | |
10 | ZHANG Y F, CHEN X. Explainable recommendation: a survey and new perspectives[J]. Foundations and Trends in Information Retrieval, 2020, 14( 1): 1- 101. 10.1561/1500000066 |
11 | RAWAT S, TYAGI U, SINGHAL S. Recommender systems in e-commerce and their challenges[C]// Proceedings of the 2021 3rd International Conference on Advances in Computing, Communication Control and Networking. Piscataway: IEEE, 2021: 1598- 1601. 10.1109/icac3n53548.2021.9725681 |
12 | ROY A, BANERJEE S, SARKAR M, et al. Exploring new vista of intelligent collaborative filtering: a restaurant recommendation paradigm[J]. Journal of Computational Science, 2018, 27( 1): 168- 182. 10.1016/j.jocs.2018.05.012 |
13 | XIAO J, YE H, HE X, et, al. Attentional factorization machines: learning the weight of feature interactions via attention networks [C]// Proceedings of the 26th International Joint Conference on Artificial Intelligence. Menlo Park, CA: AAAI Press, 2017: 3119- 3125. 10.24963/ijcai.2017/435 |
14 | TAO Y Y, JIA Y L, WANG N, et al. The FacT: taming latent factor models for explainability with factorization trees[C]// Proceedings of the 42nd International ACM SIGIR Conference on Research and Development in Infromation Retrieval. New York: ACM, 2019: 295- 304. 10.1145/3331184.3331244 |
15 | GAO J Y, WANG X T, WANG Y S, et al. Explainable recommendation through attentive multi-view learning[C]// Proceedings of the 33rd AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press, 2019: 3622- 3629. 10.1609/aaai.v33i01.33013622 |
16 | COSTA F, OUYANG S, DOLOG P, et al. Automatic generation of natural language explanations [C]// Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion. New York: ACM, 2018: No.57. 10.1145/3180308.3180366 |
17 | LI P J, WANG Z H, REN Z C, et al. Neural rating regression with abstractive tips generation for recommendation[C]// Proceedings of the 40th International ACM SIGIR Conference on Research and Development in Information Retrieval. New York: ACM, 2017: 345- 354. 10.1145/3077136.3080822 |
18 | LU Y C, DONG R H, SMYTH B. Why I like it: multi-task learning for recommendation and explanation[C]// Proceedings of the RecSys 12th ACM Conference on Recommender Systems. New York: ACM, 2018: 4- 12. 10.1145/3240323.3240365 |
19 | SEO S, HUANG J, YANG H, et al. Interpretable convolutional neural networks with dual local and global attention for review rating prediction[C]// Proceedings of the 11th ACM Conference on Recommender Systems. New York: ACM, 2017: 297- 305. 10.1145/3109859.3109890 |
20 | CHANG C, MIN Z, LIU Y Q, et al. Neural attentional rating regression with review-level explanations[C]// Proceedings of the 27th International World Wide Web Conference. New York: ACM, 2018: 1583- 1592. 10.1145/3178876.3186070 |
21 | LIU S, DEMIREL M F, LIANG Y. N-gram graph: simple unsupervised representation for graphs with applications to molecules[C]// Proceedings of the 33rd International Conference on Neural Information Processing Systerms. Red Hook, NY: Curran Associates Inc., 2019: 8466- 8478. |
22 | JI S, SATISH N, LI S, et al. Parallelizing Word2Vec in shared and distributed memory[J]. IEEE Transactions on Parallel and Distributed Systems, 2019, 30( 6): 2090- 2100. 10.1109/tpds.2019.2904058 |
23 | 陶文彬, 钱育蓉, 张伊扬, 等. 基于自编码器的深度聚类算法综述[J]. 计算机工程与应用, 2022, 58( 18): 16- 25. 10.3778/j.issn.1002-8331.2204-0049 |
TAO W B, QIAN Y R, ZHANG Y Y, et al. Survey of deep clustering algorithms based on autoencoder [J] Computer Engineering and Applications, 2022, 58( 18): 16- 25. 10.3778/j.issn.1002-8331.2204-0049 | |
24 | CHO K, VAN MERRIËNBOER B, GU̇LÇEHRE Ç, et al. Learning phrase representations using RNN encoder-decoder for statistical machine translation[C]// Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing. Stroudsburg: ACL, 2014: 1724- 1734. 10.3115/v1/d14-1179 |
25 | 梁志贞, 张磊. 面向Kullback-Leibler散度不确定集的正则化线性判别分析[J]. 自动化学报, 2022, 48( 4): 1033- 1047. 10.16383/j.aas.c210434 |
LIANG Z Z, ZHANG L. Regularized linear discriminant analysis based on uncertainty sets from Kullback-Leibler divergence[J]. Acta Automatica Sinica, 2022, 48( 4): 1033- 1047. 10.16383/j.aas.c210434 | |
26 | SALAKHUTDINOV R, MNIH A. Probabilistic matrix factorization[C]// Proceedings of the 20th International Conference on Neural Information Processing Systems. Red Hook, NY: Curran Associates Inc., 2007: 1257- 1264. 10.1145/1390156.1390267 |
27 | 陈佩武, 束方兴. 基于SVD++隐语义模型的信任网络推荐算法[J]. 大数据, 2021, 7( 4): 105- 116. 10.11959/issn.2096-0271.2021041 |
CHEN P W, SHU F X. A recommender algorithm based on SVD++ model under trust network[J]. Big Data Research, 2021, 7( 4): 105- 116. 10.11959/issn.2096-0271.2021041 | |
28 | ZHENG L, NOROOZI V, YU P S. Joint deep modeling of users and items using reviews for recommendation[C]// Proceedings of the 10th ACM International Conference on Web Search and Data Mining. New York: ACM, 2017: 425- 434. 10.1145/3018661.3018665 |
29 | WANG X, HE X N, FENG F L, et al. TEM: tree-enhanced embedding model for explainable recommendation[C]// Proceedings of the 2018 World Wide Web Conference. Republic and Canton of Geneva, Switzerland: International World Wide Web Conferences Steering Committee, 2018: 1543- 1552. 10.1145/3178876.3186066 |
30 | DENG Z H, HUANG L, WANG C D, et al. DeepCF: a unified framework of representation learning and matching functionlearning in recommender system[C]// Proceedings of the 2019 33rd AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press, 2019: 61- 68. 10.1609/aaai.v33i01.330161 |
31 | CHEN X, ZHANG Y F, QIN Z. Dynamic explainable recommendation based on neural attentive models[C]// Proceedings of the 33rd AAAI Conference on Artificial Intelligence. Palo Alto, CA: AAAI Press, 2019: 53- 60. 10.1609/aaai.v33i01.330153 |
[1] | Ziyi HE, Yan YANG, Yiling ZHANG. Multi-view clustering network with deep fusion [J]. Journal of Computer Applications, 2023, 43(9): 2651-2656. |
[2] | Hao YANG, Yi ZHANG. Feature pyramid network algorithm based on context information and multi-scale fusion importance awareness [J]. Journal of Computer Applications, 2023, 43(9): 2727-2734. |
[3] | Guolong YUAN, Yujin ZHANG, Yang LIU. Image tampering forensics network based on residual feedback and self-attention [J]. Journal of Computer Applications, 2023, 43(9): 2925-2931. |
[4] | Juntao CHEN, Ziqi ZHU. Image copy-move forgery detection based on multi-scale feature extraction and fusion [J]. Journal of Computer Applications, 2023, 43(9): 2919-2924. |
[5] | Hong WANG, Qing QIAN, Huan WANG, Yong LONG. Lightweight image tamper localization algorithm based on large kernel attention convolution [J]. Journal of Computer Applications, 2023, 43(9): 2692-2699. |
[6] | Meijia LIANG, Xinwu LIU, Xiaopeng HU. Small target detection algorithm for train operating environment image based on improved YOLOv3 [J]. Journal of Computer Applications, 2023, 43(8): 2611-2618. |
[7] | Jinghong WANG, Zhixia ZHOU, Hui WANG, Haokang LI. Attribute network representation learning with dual auto-encoder [J]. Journal of Computer Applications, 2023, 43(8): 2338-2344. |
[8] | Xiaolin LI, Songjia YANG. Hybrid beamforming for multi-user mmWave relay networks using deep learning [J]. Journal of Computer Applications, 2023, 43(8): 2511-2516. |
[9] | Shengwei DUAN, Xinyu CHENG, Haozhou WANG, Fei WANG. Dam surface disease detection algorithm based on improved YOLOv5 [J]. Journal of Computer Applications, 2023, 43(8): 2619-2629. |
[10] | Yuan LIU, Yongquan DONG, Rui JIA, Haolin YANG. Hierarchical and phased attention network model for personalized course recommendation [J]. Journal of Computer Applications, 2023, 43(8): 2358-2363. |
[11] | Yi WANG, Jie XIE, Jia CHENG, Liwei DOU. Review of object pose estimation in RGB images based on deep learning [J]. Journal of Computer Applications, 2023, 43(8): 2546-2555. |
[12] | Xiang GUO, Wengang JIANG, Yuhang WANG. Encrypted traffic classification method based on improved Inception-ResNet [J]. Journal of Computer Applications, 2023, 43(8): 2471-2476. |
[13] | Yumeng CUI, Jingya WANG, Xiaowen LIU, Shangyi YAN, Zhizhong TAO. General text classification model combining attention and cropping mechanism [J]. Journal of Computer Applications, 2023, 43(8): 2396-2405. |
[14] | Ailing QI, Xuanlin WANG. Fine-grained image recognition based on mid-level subtle feature extraction and multi-scale feature fusion [J]. Journal of Computer Applications, 2023, 43(8): 2556-2563. |
[15] | Kun ZHANG, Fengyu YANG, Fa ZHONG, Guangdong ZENG, Shijian ZHOU. Source code vulnerability detection based on hybrid code representation [J]. Journal of Computer Applications, 2023, 43(8): 2517-2526. |
Viewed | ||||||
Full text |
|
|||||
Abstract |
|
|||||