iZone: Efficient Influence Zone Evaluation over Geo-Textual Data

• Published in: 2018 IEEE 34th International Conference on Data Engineering (ICDE) pp. 1645 - 1648
• Main Authors: Qing Liu, Zijin Feng, Xike Xie, Jianliang Xu, Xin Lin, Jensen, Christian S.
• Format: Conference Proceeding
• Language: English
• Published: IEEE 01-04-2018
• Subjects: Browsers; Computer architecture; Computer science; Demonstration; Geo textual data; Indexes; Influence zone; Keyword search; Planning; Servers
• ISSN: 2375-026X
• DOI: 10.1109/ICDE.2018.00197

Owing to the widespread use of location-aware devices and the increased popularity of micro-blogging applications, we are witnessing a rapid proliferation of geo-textual data. In this demonstration, we present iZone, an efficient system for determining influence zones over geo-textual data. Specifically, iZone allows users to browse geo-textual objects, evaluate the influence zones of specified geo-textual objects, and obtain explanations of the evaluation results. The iZone system adopts a browser-server model. The server side integrates two types of spatial keyword search, namely top-k spatial keyword query and reverse top-k keyword-based location query, to support the functionality of the system. A variety of spatial indexes are employed to enhance the efficiency of the system. The browser side provides a map-based GUI interface, which enables convenient and user-friendly interaction with the system. Using a real hotel dataset from Hong Kong, iZone offers hands-on experience with influence zone evaluation in real-life applications.