Google Research Introduces ME-POIs: A Mobility-Informed Framework that Adds “How a Place Is Used” to Text-Based POI Embeddings
Summary
<p>framework that folds aggregate human movement into text-based place embeddings. Language models describe what a place is; they miss how it is used. ME-POIs encodes each visit as a contextualized vector and aligns it with one learnable prototype per POI through contrastive learning, then transfers visit distributions from data-rich anchors to the long tail across three spatial scales. Across five map-enrichment tasks on Los Angeles and Houston mobility data, adding ME-POIs improved 34 of 35 model-task pairings in Los Angeles — up to 81.9% relative F1 on visit intent and a 24.7% MAE reduction on busyness. A mobility-only variant beat Gemini text embeddings on price-level classification.</p> <p>The post <a href="https://www.marktechpost.com/2026/08/24/google-research-introduces-me-pois-a-mobility-informed-framework-that-adds-how-a-place-is-used-to-text-based-poi-embeddings/">Google Research Introduces ME-POIs: A Mobility-Informed Framework that Adds “How a Place Is Used” to Text-Based POI Embeddings</a> appeared first on <a href="https://www.marktechpost.com">MarkTechPost</a>.</p>