Location-Based Instant Search

Location-based keyword search has become an important part of our daily life. Such a query asks for records satisfying both a spatial condition and a keyword condition. State-of-the-art techniques extend a spatial tree structure by adding keyword information. In this paper we study location-based instant search, where a system searches based on a partial query a user has typed in. We first develop a new indexing technique, called filtering-effective hybrid index (FEH), that judiciously uses two types of keyword filters based on their selectiveness to do powerful pruning. Then, we develop indexing and search techniques that store prefix information on the FEH index and efficiently answer partial queries. Our experiments show a high efficiency and scalability of these techniques.