Using Aggregate Location Metadata to Provide a Personalized Service

Functionality is described herein which generates a plurality of item models based on the aggregate behavior of users, such as the aggregate behavior of the users in selecting network-accessible sites and/or issuing particular queries. In one implementation, each item model estimates a probabilistic distribution of locations for an individual, given that the individual selects a particular item (eg, a particular site or query). The functionality can use the item models to provide a personalized service to an end user. For example, in one scenario, the functionality can generate a plurality of location-based features based on the item models. The functionality can then learn a ranking model based on the location-based features. In a real-time phase of operation, a query processing system uses the ranking model to personalize search results for an end user.