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Location-Based Top-k Term Querying over Sliding Window

  • Ying Xu
  • Lisi Chen
  • Bin YaoEmail author
  • Shuo ShangEmail author
  • Shunzhi Zhu
  • Kai Zheng
  • Fang Li
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10569)

Abstract

In part due to the proliferation of GPS-equipped mobile devices, massive svolumes of geo-tagged streaming text messages are becoming available on social media. It is of great interest to discover most frequent nearby terms from such tremendous stream data. In this paper, we present novel indexing, updating, and query processing techniques that are capable of discovering top-k locally popular nearby terms over a sliding window. Specifically, given a query location and a set of geo-tagged messages within a sliding window, we study the problem of searching for the top-k terms by considering both the term frequency and the proximities between the messages containing the term and the query location. We develop a novel and efficient mechanism to solve the problem, including a quad-tree based indexing structure, indexing update technique, and a best-first based searching algorithm. An empirical study is conducted to show that our proposed techniques are efficient and fit for users’ requirements through varying a number of parameters.

Keywords

Top-k Term Location 

Notes

Acknowledgement

This work was supported by the NSFC (U1636210, 61373156, 91438121 and 61672351), the National Basic Research Program (973 Program, No. 2015CB352403), the National Key Research and Development Program of China (2016YFB0700502), the Scientific Innovation Act of STCSM (15JC1402400) and the Microsoft Research Asia.

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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  1. 1.Shanghai Jiao Tong UniversityShanghaiChina
  2. 2.Hong Kong Baptist UniversityHong KongChina
  3. 3.King Abdullah University of Science and TechnologyThuwalSaudi Arabia
  4. 4.Xiamen University of TechnologyXiamenChina
  5. 5.Soochow UniversitySoochowChina

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