Accesso libero

An Accuracy Study of Personalized Recommendation System for E-commerce Based on Big Data Analysis

   | 05 ago 2024
INFORMAZIONI SU QUESTO ARTICOLO

Cita

Patro, S. G. K., Mishra, B. K., & Panda, S. K. (2022). Hybrid action-allied recommender mechanism: an unhackneyed attribute for ecommerce. ECS transactions(1), 107. Search in Google Scholar

Jannach, D., Ludewig, M., & Lerche, L. (2017). Session-based item recommendation in e-commerce. User Modeling and User-Adapted Interaction. Search in Google Scholar

Xiaojun, L. (2017). An improved clustering-based collaborative filtering recommendation algorithm. Cluster Computing, 20(2), 1281-1288. Search in Google Scholar

Márcio Guia, Silva, R. R., & Bernardino, J. (2019). A hybrid ontology-based recommendation system in e-commerce. Algorithms, 12(11), 239. Search in Google Scholar

Cai, J. (2017). Research on personalized recommendation algorithm in e-commerce based on hybrid algorithm. C e Ca, 42(2), 590-594. Search in Google Scholar

Choi, Y., & Kim, S. K. (2018). A recommendation system for repetitively purchasing items in e-commerce based on collaborative filtering and association rules. Journal of Internet Technology, 19, 1691-1698. Search in Google Scholar

Lv, J., Song, B., Guo, J., Du, X., & Guizani, M. (2019). Interest-related item similarity model based on multimodal data for top-n recommendation. IEEE Access, 1-1. Search in Google Scholar

Zhang, J., Zhang, C., & Yu, H. (2018). Research on e-commerce intelligent service based on data mining. MATEC Web of Conferences, 173(3), 03012. Search in Google Scholar

Li, Z., Amagata, D., Zhang, Y., Maekawa, T., Hara, T., & Yonekawa, K., et al. (2022). Hml4rec: hierarchical meta-learning for cold-start recommendation in flash sale e-commerce. Knowledge-based systems. Search in Google Scholar

Jiao, W., & Li, J. (2017). Information recommendation system based on collaborative filtering in cloud computing. Boletin Tecnico/Technical Bulletin, 55(7), 98-104. Search in Google Scholar

Zeng, Y., Song, S., & Peng, W. (2022). Optimal add-on items recommendation service strength strategy for e-commerce platform with full-reduction-promotion. RAIRO - Operations Research, 56(2), 1031-1049. Search in Google Scholar

Zhang, N. (2018). A personalized recommendation algorithm based on text mining. International Journal of Performability Engineering, 14(7), 1401-1410. Search in Google Scholar

Wang, B., Ye, F., & Xu, J. (2018). A personalized recommendation algorithm based on the user’s implicit feedback in e-commerce. Future Internet, 10(12), 117. Search in Google Scholar

Cui, Y. (2021). Intelligent recommendation system based on mathematical modeling in personalized data mining. Mathematical Problems in Engineering, 2021(3), 1-11. Search in Google Scholar

Li, W., Zhou, X., Shimizu, S., Xin, M., Jiang, J., & Gao, H., et al. (2019). Personalization recommendation algorithm based on trust correlation degree and matrix factorization. IEEE Access, 1-1. Search in Google Scholar

Kaur, B., & Rani, S. (2023). Are the customers receiving exact recommendations from the e-commerce companies? towards the identification of gray sheep users using personality parameters. International Journal of Performability Engineering(7), 19. Search in Google Scholar

Hu, Z. H., Li, X., Wei, C., & Zhou, H. L. (2019). Examining collaborative filtering algorithms for clothing recommendation in e-commerce:. Textile Research Journal, 89(14), 2821-2835. Search in Google Scholar

Alrumiah, S. S., & Hadwan, M. (2021). Implementing big data analytics in e-commerce: vendor and customer view. IEEE Access, PP(99), 1-1. Search in Google Scholar

Jia, Z. (2017). Cross-border e-commerce personalized filtering recommendation model based on particle-level compression awareness. Boletin Tecnico/Technical Bulletin, 55(7), 136-143. Search in Google Scholar

Yan, C., Chen, Y., & Zhou, L. (2019). Differentiated fashion recommendation using knowledge graph and data augmentation. IEEE Access, PP(99), 1-1. Search in Google Scholar

Bagga, V., Sugunan, S., Srivastava, A., Kumar, R., Gupta, A., & Kumar, D., et al. (2023). Adaptive fusion and transfer learning for enhanced e –commerce recommendations. Procedia Computer Science, 229, 345-356. Search in Google Scholar

Wenjun Liu,Yuyan Sun,Bao Yu,Hailan Wang,Qingcheng Peng,Mengshu Hou.. & Cheng Liu.(2024).Automatic Text Summarization Method Based on Improved TextRank Algorithm and K-Means Clustering.Knowledge-Based Systems111447-. Search in Google Scholar

Qiu, Dong & Zheng, Qin.(2021).Improving TextRank Algorithm for Automatic Keyword Extraction with Tolerance Rough Set.International Journal of Fuzzy Systems(3),1-11. Search in Google Scholar

Ni Li & Yinshui Xia.(2024).Movie recommendation based on ALS collaborative filtering recommendation algorithm with deep learning model.Entertainment Computing100715-. Search in Google Scholar

Sheng Jinfang, Liu Qingqing, Hou Zhengang & Wang Bin. (2023). A Collaborative Filtering Recommendation Algorithm Based on Community Detection and Graph Neural Network.Neural Processing Letters (6),7095-7112. Search in Google Scholar

Ying Yin.(2024).Research on the integration path of cultural creative industry and tourism industry based on collaborative filtering recommendation algorithm.Applied Mathematics and Nonlinear Sciences(1), Search in Google Scholar

eISSN:
2444-8656
Lingua:
Inglese
Frequenza di pubblicazione:
Volume Open
Argomenti della rivista:
Life Sciences, other, Mathematics, Applied Mathematics, General Mathematics, Physics