Key concepts of group pattern discovery algorithms from spatiooral trajectories

Karolina Dluzniak, Wei Jie, Hai Wang, Wei Xing

Research output: Chapter in Book/Report/Conference proceedingConference publication

Abstract

Over the years, the increasing development of location acquisition devices have generated a significant amount of spatiooral data. This data can be further analysed in search for some interesting patterns, new information, or to construct predictive models such as next location prediction. The goal of this paper is to contribute to the future research and development of group pattern discovery algorithms from spatiooral data by providing an insight into algorithms design in this research area which is based on a comprehensive classification of state-of-the-art models. This work includes static, big data as well as data stream processing models which to the best of authors' knowledge is the first attempt of presenting them in this context. Furthermore, currently available surveys and taxonomies in this research area do not focus on group pattern mining algorithms nor include the state-of-the-art models. The authors conclude with the proposal of a conceptual model of Universal, Streaming, Distributed and Parameter-light (USDP) algorithm that addresses current challenges in this research area.

Original languageEnglish
Title of host publicationProceedings - 15th International Conference on Semantics, Knowledge and Grids
Subtitle of host publicationOn Big Data, AI and Future Interconnection Environment, SKG 2019
EditorsHai Zhuge, Xiaoping Sun
PublisherIEEE
Pages190-197
Number of pages8
ISBN (Electronic)9781728158235
DOIs
Publication statusPublished - 23 Mar 2020
Event2019 15th International Conference on Semantics, Knowledge and Grids (SKG) - Guangzhou, China
Duration: 17 Sep 201918 Sep 2019

Publication series

NameProceedings - 15th International Conference on Semantics, Knowledge and Grids: On Big Data, AI and Future Interconnection Environment, SKG 2019

Conference

Conference2019 15th International Conference on Semantics, Knowledge and Grids (SKG)
Period17/09/1918/09/19

Keywords

  • Clustering
  • Distributed trajectory mining
  • Spatiooral data mining

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