ACM RecSys 2018 Late-Breaking Results Proceedings
The ACM RecSys'18 Late-Breaking Results track (previously known as the Poster track) is part of the main program of the 2018 ACM Conference on Recommender Systems in Vancouver, Canada. The track attracted 48 submissions this year out of which 18 papers could be accepted resulting in an acceptance rated of 37.5%.
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Recommendation SystemsSimilar Papers 제목 키워드 기반
The Potential of AutoML for Recommender Systems
Automated Machine Learning (AutoML) has greatly advanced applications of Machine Learning (ML) including model compression, machine translation, and computer vision. Recommender Systems (RecSys) can be seen as an applica…
AutoMLMachine TranslationModel CompressionRecommendation SystemsAnalysis and Optimization of GNN-Based Recommender Systems on Persistent Memory
Graph neural networks (GNNs), which have emerged as an effective method for handling machine learning tasks on graphs, bring a new approach to building recommender systems, where the task of recommendation can be formula…
Link PredictionRecommendation SystemsUser Altruism in Recommendation Systems
Users of social media platforms based on recommendation systems (RecSys) (e.g. TikTok, X, YouTube) strategically interact with platform content to influence future recommendations. On some such platforms, users have been…
Recommendation SystemsMembership Inference Attacks on In-Context Examples in LLM-based Recommender Systems
Large language models (LLMs) based recommender systems (RecSys) can adapt flexibly across different domains. It uses in-context learning (ICL), i.e., prompts, including sensitive historical user-specific item interaction…
Membership Inference Attacks on Recommender System: A Survey
Recommender systems (RecSys) have been widely applied to various applications, including E-commerce, finance, healthcare, social media and have become increasingly influential in shaping user behavior and decision-making…