output
20172023
most citedIntent Contrastive Learning for Sequential Recommendation

404 citations

Showing cs.IRShow all

6 papers · 1 filter

cs.IR202219 cited

Dynamic Causal Collaborative Filtering

Shuyuan Xu, Juntao Tan, Zuohui Fu +3

Causal graph, as an effective and powerful tool for causal modeling, is usually assumed as a Directed Acyclic Graph (DAG). However, recommender systems usually involve feedback loo…

cs.IR202225 cited

Mining Root Cause Knowledge from Cloud Service Incident Investigations for AIOps

Amrita Saha, Steven C. H. Hoi

Root Cause Analysis (RCA) of any service-disrupting incident is one of the most critical as well as complex tasks in IT processes, especially for cloud industry leaders like Salesf…

cs.IR202261 cited

Large-scale Personalized Video Game Recommendation via Social-aware Contextualized Graph Neural Network

Liangwei Yang, Zhiwei Liu, Yu Wang +3

Because of the large number of online games available nowadays, online game recommender systems are necessary for users and online game platforms. The former can discover more pote…

cs.IR202218 cited

RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems

Zohreh Ovaisi, Shelby Heinecke, Jia Li +3

Robust machine learning is an increasingly important topic that focuses on developing models resilient to various forms of imperfect data. Due to the pervasiveness of recommender s…

cs.IR202183 cited

Contrastive Self-supervised Sequential Recommendation with Robust Augmentation

Zhiwei Liu, Yongjun Chen, Jia Li +3

Sequential Recommendationdescribes a set of techniques to model dynamic user behavior in order to predict future interactions in sequential user data. At their core, such approache…

cs.IR202032 cited

CO-Search: COVID-19 Information Retrieval with Semantic Search, Question Answering, and Abstractive Summarization

Andre Esteva, Anuprit Kale, Romain Paulus +4

The COVID-19 global pandemic has resulted in international efforts to understand, track, and mitigate the disease, yielding a significant corpus of COVID-19 and SARS-CoV-2-related…