Nov 14, 2022 · We proposed a disentangled representation learning method named DIG (short for D isentangled embedding of user I nterest and POIs' G eographical information).

Abstract—Point-of-Interest (POI) recommendation has drawn a lot of attention in both academia and industry. It utilizes user check-in.

Aiming at decoupling the geographical factor and the user interest factor thoroughly, we first proposed a geo-constrained negative sampling strategy, which ...

Oct 29, 2022 · A novel Disentangled dual-graph framework for POI recommendation, which jointly utilizes sequential and geographical relationships on two separate graphs.

Jul 9, 2024 · To address challenges in disentangling geographical effect, we proposed a disentangled representation learning method named DIG (short for D ...

Feb 27, 2023 · A novel Disentangled dual-graph framework for POI recommendation, which jointly utilizes sequential and geographical relationships on two separate graphs.

Oct 29, 2022 · In this paper, we address the above challenge by proposing DisenPOI, a novel Disentangled dual-graph framework for POI recommendation, which ...

DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation PDF CODE. JCR Q1 2023. FedPOIRec: Privacy-preserving ...

Oct 10, 2023 · DisenPOI: Disentangling Sequential and Geographical Influence for Point-of-Interest Recommendation. In Proceedings of the Sixteenth ACM ...

POI recommendation is based on several factors such as location, time, familiarity with a place, social circle, and demographics. The most important factor is ...