Exploration on Similar Spatial Textual Objects Retrieval

Effective and efficient retrieval of similar spatial textual objects plays an important role for many location based applications, such as Foursquare, Yelp, and so forth. Although there are many studies exploring on this issue, most of them focus on how to integrate spatial and textual information to efficiently retrieve top-k results yet few of them address the effectiveness issue. In this paper, we propose a semantic aware strategy which can effectively and efficiently retrieve the top-k similar spatial textual objects based on a general framework. Extensive experimental evaluation demonstrates that the performance of our proposal outperforms the state-of-the-art approach.