Subject Areas : International Journal of Data Envelopment Analysis

Vahid Saffari ¹ , Karamolah BagheriFard ² , Hamid Parvin ³ , Samad Nejatian ⁴ , Vahide Rezaie ⁵

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Received: 2024-09-11 Accepted : 2024-11-21 Published : 2024-10-01

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References:

Aggarwal, C. C. (2016). Recommender Systems: The Textbook. Springer.

Cooley, R. M. (1999). Data Preparation for Mining World Wide Web Browsing Patterns. Knowledge and Information Systems 1, 5–32.

Dacrema, M. F. (2021). A Troubling Analysis of Reproducibility and Progress in Recommender Systems Research. ACM Transactions on Information Systems Volume 39, 1–49.

Fan, Y. M. (2021). Continuous-time sequential recommendation with temporal graph collaborative networks. The 30th ACM International Conference on Information and Knowledge Management.

Gao, C. G. (2020). A state-preserving RNN framework for sequential recommendation. Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining.

Gong, S. C. (2021). Contrastive self-supervised sequential recommendation with robust augmentation. Proceedings of the 30th ACM International Conference on Information and Knowledge Management (CIKM).

Li, S. W. (2020). Time interval aware self-attention for sequential recommendation. Proceedings of the 13th International Conference on Web Search and Data Mining (WSDM).

Liu, B. L. (2018). Sequence-Aware Recommender Systems: An Overview. ACM Computing Surveys (CSUR), 54(4), 1-36.

Ma, R. S. (2020). Memory augmented graph neural networks for sequential recommendation. Proceedings of the AAAI Conference on Artificial Intelligence 34(04), (pp. 5045-5052).

Mobasher, B. D. (2002). Discovery and Evaluation of Aggregate Usage Profiles for Web Personalization. Data Mining and Knowledge Discovery 6, 61-82.

N.S. (2018). Retrieved from NASA: https://www.kaggle.com/datasets/souhagaa/nasa-access-log-dataset

Navarro, G. (2021). A Guided Tour to Approximate String Matching. ACM Computing Surveys., 33.

Ricci, F. R. (2015). Recommender Systems Handbook. Springer.

S. Latifi, D. J. (2022). Sequential recommendation : A study on transformers, nearest neighbors and sampled metrics. Inf. Sci.(Ny)., vol. 609, 660–678.

Sun, F. L. (2019). BERT4Rec: Sequential Recommendation with Bidirectional Encoder Representations from Transformer. Proceedings of the 28th ACM International Conference on Information and Knowledge Management, (pp. 1441–1450).

Tan, P. N. (2018). Introduction to Data Mining. Pearson Education. Pearson.

Wang, S. Y. (2021). Denoising implicit feedback for recommendation. Proceedings of the 44th International ACM SIGIR Conference on Research and Development in Information Retrieval.

Xie, Y. Z. (2020). Sequential recommender system based on hierarchical attention network. Proceedings of the 13th ACM International Conference on Web Search and Data Mining (WSDM).

Zaker, F. (2019). Harvard Dataverse, V1. Retrieved from Online Shopping Store - Web Server Logs: https://doi.org/10.7910/DVN/3QBYB5

Zaki, M. (2020). An efficient algorithm for mining frequent sequences. Machine Learning, 42, 31–60.

Zhou, K. W. (2020). S3-Rec: Self-supervised learning for sequential recommendation with mutual information maximization. Proceedings of the 29th ACM International Conference on Information & Knowledge Management, (pp. 1893–1902).