SOPS : a system for efficient processing of spatial-keyword publish/subscribe

• Main Authors: Chen, Lisi, Cui, Yan, Cong, Gao, Cao, Xin
• Other Authors: School of Computer Engineering
• Format: Article
• Language: English
• Published: 2014
• Subjects: DRNTU::Engineering::Computer science and engineering
• Online Access: https://hdl.handle.net/10356/104998; http://hdl.handle.net/10220/20434; http://www.vldb.org/2014/program/papers/demo/p1077-chen.pdf
• Institution: Nanyang Technological University

Massive amount of data that are geo-tagged and associated with text information are being generated at an unprecedented scale. These geo-textual data cover a wide range of topics. Users are interested in receiving up-to-date geo-textual objects (e.g., geo-tagged Tweets) such that their locations meet users' need and their texts are interesting to users. For example, a user may want to be updated with tweets near her home on the topic "dengue fever headache." In this demonstration, we present SOPS, the Spatial-Keyword Publish/Subscribe System, that is capable of efficiently processing spatial keyword continuous queries. SOPS supports two types of queries: (1) Boolean Range Continuous (BRC) query that can be used to subscribe the geo-textual objects satisfying a boolean keyword expression and falling in a specified spatial region; (2) Temporal Spatial-Keyword Top-k Continuous (TaSK) query that continuously maintains up-to-date top-k most relevant results over a stream of geo-textual objects. SOPS enables users to formulate their queries and view the real-time results over a stream of geotextual objects by browser-based user interfaces. On the server side, we propose solutions to efficiently processing a large number of BRC queries (tens of millions) and TaSK queries over a stream of geo-textual objects.