Dingming Wu
Christian S. Jensen
ABSTRACT
Spatial keyword queries retrieve spatial textual objects that are near a query location and are relevant to query keywords. The paper defines the top-k spatial textual clusters (k-STC) query that returns the top-k clusters that are located close to a given query location, contain relevant objects with regard to given query keywords, and have an object density that exceeds a given threshold. This query aims to support users who wish to explore nearby regions with many relevant objects. To compute this query, the paper proposes a basic and an advanced algorithm that rely on on-line density-based clustering. An empirical study offers insight into the performance properties of the proposed algorithms.
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Index Terms
- A Density-Based Approach to the Retrieval of Top-K Spatial Textual Clusters
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