An efficient query indexing mechanism for filtering geo-textual data

• Main Authors: Chen, Lisi, Cong, Gao, Cao, Xin
• Other Authors: School of Computer Engineering
• Format: Conference or Workshop Item
• Language: English
• Published: 2013
• Subjects: DRNTU::Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/98593; http://hdl.handle.net/10220/17341
• Institution: Nanyang Technological University

Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. Users may want to be notified of interesting geo-textual objects during a period of time. For example, a user may want to be informed when tweets containing term "garage sale" are posted within 5 km of the user's home in the next 72 hours. In this paper, for the first time we study the problem of matching a stream of incoming Boolean Range Continuous queries over a stream of incoming geo-textual objects in real time. We develop a new system for addressing the problem. In particular, we propose a hybrid index, called IQ-tree, and novel cost models for managing a stream of incoming Boolean Range Continuous queries. We also propose algorithms for matching the queries with incoming geo-textual objects based on the index. Results of empirical studies with implementations of the proposed techniques demonstrate that the paper's proposals offer scalability and are capable of excellent performance.