4 papers
Guess Where You Go: Generative Next Point-of-Interest Recommendation in Amap
Penglong Zhai, Bowen Zheng, Jie Li +8
Generative retrieval enables recommender systems to retrieve items by generating compact item identifiers, but scaling it to industrial scenarios remains challenging due to redunda…
Generative Spatiotemporal Intent Sequence Recommendation via Implicit Reasoning in Amap
Sicong Wang, Ruiting Dong, Yue Liu +7
Real-world user behavior rarely consists of isolated actions; instead, it often forms intent flows governed by spatiotemporal dependencies. To provide integrated service recommenda…
Cognitive-Aligned Spatio-Temporal Large Language Models For Next Point-of-Interest Prediction
Penglong Zhai, Jie Li, Fanyi Di +9
The next point-of-interest (POI) recommendation task aims to predict the users' immediate next destinations based on their preferences and historical check-ins, holding significant…
A Simple Contrastive Framework Of Item Tokenization For Generative Recommendation
Penglong Zhai, Yifang Yuan, Fanyi Di +7
Generative retrieval-based recommendation has emerged as a promising paradigm aiming at directly generating the identifiers of the target candidates. However, in large-scale recomm…