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…
GeoGR: A Generative Retrieval Framework for Spatio-Temporal Aware POI Recommendation
Fangye Wang, Haowen Lin, Yifang Yuan +4
Next Point-of-Interest (POI) prediction is a fundamental task in location-based services, especially critical for large-scale navigation platforms like AMAP that serve billions of…
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…