Location-Based services guide a user to find the object which provides services located in a particular position or region (e.g., looking for a coffee shop near a university). Given a query location and multiple keywords, location-based services return the most relevant objects ranked according to location proximity and text relevancy. Various hybrid indexes have been proposed in recent years which combine R-tree and inverted index to improve query efficiency. Unfortunately, the state-of-the-art approaches require more space in order to reduce response time. Cache mechanism is inefficient due to huge storage overhead. In this paper, a novel index based on index compressed technology (CSTI) is proposed, to answer top-k SKQ. CSTI significantly reduces storage overhead (by at least 80%), while maintaining efficient query performance. Extensive experiments based on real dataset and simulated dataset confirm CSTI is effective and efficient.