Efficient Batch Top k Spatial Term Search by Feature Redundancy

Due to the rapid rise in the geo-positioning technologies and location based services, millions of spatio textual objects are collected in many applications like social networks, geo location services that has been attracted many research communities. Each spatial objects is described by its spatial locations (latitude, longitude) and a set of query Terms. In this paper, we propose a framework called Efficient Batch Top k Spatial Term (Keyword) Search by Feature Redundancy (k STFR), that retrieves top k results for the batch of queries. The clusters and subclusters are constructed based on the computed range and category of the object present in the user query. Experiments are conducted on Geographic Names (GN) dataset. Experiments results shows that our proposed method outperforms Inverted Linear Quadtree (ILQ) [1] efficiently and also support batch of queries with improved response time.