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Spatial semantic search in location-based web services

As GPS-enabled mobile devices have advanced, the location-based service(LBS) became one of the most active subjects in the Web-based services. Major Web-based services such as Google Picasa, Twitter, Facebook, and Flicker employ LBS as one of their main features. Consequently, a large number of geotagged documents are generated by users in the Web-based services. Recently, there have been studies on the spatial keyword search which aims to find a set of documents in the Web-based services by evaluating the spatial relevance and keyword relevance. It is a combination of the spatial search and keyword search, each of which has been studied for a long time. In this paper, we address the spatial semantic search problem which is to find top k relevant sets of documents with spatial constraints and semantic constraints. For devising an effective solution of the spatial semantic search, we propose a hybrid index strategy, a ranking model and an efficient search algorithm. In addition, we present the current status of our research progress, and discuss remaining challenges and future works.