SOPS

Abstract

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". AB@In this demonstration, we present SOPS, the <u>S</u>patial-Keyw<u>o</u>rd <u>P</u>ublish/<u>S</u>ubscribe System, that is capable of efficiently processing spatial keyword continuous queries. SOPS supports two types of queries: (1) <u>B</u>oolean <u>R</u>ange <u>C</u>ontinuous (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) <u>T</u>empor<u>a</u>l <u>S</u>patial-<u>K</u>eyword 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 geo-textual 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.