iZone: Efficient Influence Zone Evaluation over Geo-Textual Data

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.

[1]  Jianliang Xu,et al.  Reverse Keyword-Based Location Search , 2017, 2017 IEEE 33rd International Conference on Data Engineering (ICDE).

[2]  Kian-Lee Tan,et al.  Efficient safe-region construction for moving top-K spatial keyword queries , 2012, CIKM.

[3]  Jiaheng Lu,et al.  Reverse spatial and textual k nearest neighbor search , 2011, SIGMOD '11.

[4]  Muhammad Aamir Cheema,et al.  Influence zone: Efficiently processing reverse k nearest neighbors queries , 2011, 2011 IEEE 27th International Conference on Data Engineering.

[5]  S. Muthukrishnan,et al.  Influence sets based on reverse nearest neighbor queries , 2000, SIGMOD '00.

[6]  Christian S. Jensen,et al.  Efficient Retrieval of the Top-k Most Relevant Spatial Web Objects , 2009, Proc. VLDB Endow..

[7]  Jianliang Xu,et al.  Answering why-not spatial keyword top-k queries via keyword adaption , 2016, 2016 IEEE 32nd International Conference on Data Engineering (ICDE).

[8]  Christian S. Jensen,et al.  Efficient continuously moving top-k spatial keyword query processing , 2011, 2011 IEEE 27th International Conference on Data Engineering.