Locations are often expressed in physical coordinates such as an [X, Y ] tuple in some coordinate system. Unfortunately, a vast majority of location-based applications desire the semantic translation of coordinates, i.e., store-names like Starbucks, Macy’s, Panera. Past work has mostly focused on achieving localization accuracy, while assuming that the translation of physical to semantic coordinates will be done manually. In this paper, we explore an opportunity for automatic semantic localization – the presence of a website corresponding to each physical store. We propose to correlate the information seen in a physical store with that found in websites of the stores around that location, to recognize that store. Specifically, we assume a repository of crowdsourced WiFi-tagged pictures from different stores. By correlating words inside the pictures, against words extracted from store websites, our proposed system can automatically label clusters of pictures, and the corresponding ...