THUDM/NLP4Rec-Papers
Paper list of NLP for recommender systems
This is a curated collection of academic papers exploring how natural language processing (NLP) techniques can enhance recommender systems. It organizes research on topics like using knowledge graphs for recommendations, generating text ads, conversational interfaces, and explainable recommendations. This resource is for researchers, data scientists, and engineers working on building more sophisticated and user-friendly recommendation engines.
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Use this if you are researching or developing advanced recommender systems and want to understand the latest academic breakthroughs at the intersection of NLP and recommendations.
Not ideal if you are looking for ready-to-use code, software libraries, or a simple guide to implement basic recommendation algorithms.
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Nov 13, 2019
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