mengfeizhang820/Paperlist-for-Recommender-Systems

Organizes peer-reviewed papers across recommender systems subdisciplines including collaborative filtering, content-aware methods, session-based systems, and explainability—each entry links to published PDFs and implementation code. Emphasizes neural and graph-based approaches (NCF, GCN, autoencoders) over traditional matrix factorization, with coverage spanning explicit feedback, implicit signals, and contrastive learning paradigms. Spans major venues (SIGIR, KDD, WWW, AAAI, RecSys) from 2016–2021 and includes both English and Chinese survey papers.

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