Skype

Author:

Wang Xiang1,Zhang Ying2,Zhang Wenjie1,Lin Xuemin3,Huang Zengfeng1

Affiliation:

1. University of New South Wales, Australia

2. University of Technology Sydney, Australia

3. East China Normal University, China and University of New South Wales, Australia

Abstract

As the prevalence of social media and GPS-enabled devices, a massive amount of geo-textual data has been generated in a stream fashion, leading to a variety of applications such as location-based recommendation and information dissemination. In this paper, we investigate a novel real-time top- k monitoring problem over sliding window of streaming data; that is, we continuously maintain the top-k most relevant geo-textual messages (e.g., geo-tagged tweets) for a large number of spatial-keyword subscriptions (e.g., registered users interested in local events ) simultaneously. To provide the most recent information under controllable memory cost, sliding window model is employed on the streaming geo-textual data. To the best of our knowledge, this is the first work to study top- k spatial-keyword publish/subscribe over sliding window. A novel system, called Skype (Top-k Spatial-keyword Publish/Subscribe), is proposed in this paper. In Skype, to continuously maintain top- k results for massive subscriptions, we devise a novel indexing structure upon subscriptions such that each incoming message can be immediately delivered on its arrival. Moreover, to reduce the expensive top- k re-evaluation cost triggered by message expiration, we develop a novel cost-based k-skyband technique to reduce the number of re-evaluations in a cost-effective way. Extensive experiments verify the great efficiency and effectiveness of our proposed techniques.

Publisher

VLDB Endowment

Subject

General Earth and Planetary Sciences,Water Science and Technology,Geography, Planning and Development

Cited by 63 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. SkyEye: continuous processing of moving spatial-keyword queries over moving objects;GeoInformatica;2024-03-20

2. Continuous Similarity Search for Dynamic Text Streams;IEICE Transactions on Information and Systems;2023-12-01

3. STAR: A Cache-based Stream Warehouse System for Spatial Data;ACM Transactions on Spatial Algorithms and Systems;2023-11-20

4. Processing of Spatial-Keyword Range Queries in Apache Spark;Proceedings of the 11th ACM SIGSPATIAL International Workshop on Analytics for Big Geospatial Data;2023-11-13

5. Approximate Reverse Top-k Spatial-Keyword Queries;2023 24th IEEE International Conference on Mobile Data Management (MDM);2023-07

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