DFRec: Dual Fluctuation Modeling of Multi-level Intent Evolution for Next-Item Recommendation
Nengjun Zhu, Lingdan Sun, Qi Zhang, Jian Cao, Hang Yu
Abstract
User sequential behaviors are driven by a variety of complex and evolving intents. Capturing the dynamic change of user intents has become critical yet challenging in the next-item recommendation. Existing studies usually model the transition relationships among multiple intents within a session or integrate temporal information to capture the dynamic evolution of user intents. However, they struggle to identify the precise timing and magnitudes of intent changes, leading to ambiguity in providing consistent or violated recommendations and ultimately yielding subpar performance. To this end, we propose a novel framework called Dual Fluctuation Modeling of Multi-level Intent Evolution for Next-Item Recommendation (DFRec) in this paper. DFRec explicitly identifies the user intent changes and further quantifies the magnitude of the changes. Specifically, we assume that a user
BibTeX
@inproceedings{aaai2026_dfrecdualfluctua,
title = {DFRec: Dual Fluctuation Modeling of Multi-level Intent Evolution for Next-Item Recommendation},
author = {Nengjun Zhu and Lingdan Sun and Qi Zhang and Jian Cao and Hang Yu},
booktitle = {AAAI 2026},
year = {2026}
}