Apr 25, 2022 · This is the first work on debiased sequential recommendation. We conduct extensive experiment based on both synthetic and real-world datasets.

Apr 25, 2022 · Sequential recommendation holds the promise of understanding user preference by capturing successive behavior correlations.

Latent confounders---unobserved variables that influence both treatment and outcome---can bias estimates of causal effects. In some cases, these confounders are ...

Duration: 18:38
Posted: Sep 12, 2022

Unbiased Sequential Recommendation with Latent Confounders ; WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25 - 29, 2022; Year: ...

Aug 18, 2022 · We present KuaiRand, an unbiased sequential recommendation dataset containing millions of intervened interactions on randomly exposed videos.

Unbiased Sequential Recommendation with Latent Confounders (2022 WWW, IPS for seqrec) ... CauseRec: Counterfactual User Sequence Synthesis for Sequential ...

Co-authors ; Unbiased sequential recommendation with latent confounders. Z Wang, S Shen, Z Wang, B Chen, X Chen, JR Wen. Proceedings of the ACM Web Conference ...

Unbiased Sequential Recommendation with Latent Confounders. In Proceedings of the ACM Web Conference 2022 (pp. 2195-2204). IPW, WWW, 2022, N/A. InvPref, Wang, Z ...

May 24, 2024 · Recommender systems suffer from confounding biases when there exist confounders affecting both item features and user feedback (e.g., like or ...