4 papers · 1 filter
SPAR: Enhancing Industrial-Scale Generative POI Recommendation via Real-World Spatial Perception
Fangye Wang, Yunjin Gu, Haowen Lin +4
Generative Point-of-Interest (POI) recommendation, autoregressively generating a target POI's semantic ID (SID), holds great promise for Location-Based Services, where a recommenda…
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: Enabling Spatio-Temporal Aware Industrial-scale Generative POI Recommendations
Fangye Wang, Haowen Lin, Yifang Yuan +4
Next Point-of-Interest (POI) prediction is a fundamental task in location-based services (LBS), especially critical for large-scale navigation platforms such as AMAP that serve bil…
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…