Visualet: Visualizing Shapelets for Time Series Classification

Guozhong Li, Koon Kau CHOI, Sourav S. Bhowmick, Grace Lai Hung Wong, Kwok Pan CHUN, Shiwen Li

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

Abstract

Time series classification (TSC) has attracted considerable attention from both academia and industry. TSC methods that are based on shapelets (intuitively, small highly-discriminative subsequences have been found effective and are particularly known for their interpretability, as shapelets themselves are subsequences. A recent work has significantly improved the efficiency of shapelet discovery. For instance, the shapelets of more than 65% of the datasets in the UCR Archive (containing data from different application domains) can be computed within an hour, whereas those of 12 datasets can be computed within a minute. Such efficiency has made it possible for demo attendees to interact with shapelet discovery and explore high-quality shapelets. In this demo, we present Visualet - a tool for visualizing shapelets, and exploring effective and interpretable ones.

Original languageEnglish
Title of host publicationCIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages3429-3432
Number of pages4
ISBN (Electronic)9781450368599
DOIs
Publication statusPublished - 19 Oct 2020
Event29th ACM International Conference on Information and Knowledge Management, CIKM 2020 - Virtual, Online, Ireland
Duration: 19 Oct 202023 Oct 2020

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference29th ACM International Conference on Information and Knowledge Management, CIKM 2020
Country/TerritoryIreland
CityVirtual, Online
Period19/10/2023/10/20

Scopus Subject Areas

  • Business, Management and Accounting(all)
  • Decision Sciences(all)

User-Defined Keywords

  • accuracy
  • efficiency
  • shapelet discovery
  • time-series classification

Fingerprint

Dive into the research topics of 'Visualet: Visualizing Shapelets for Time Series Classification'. Together they form a unique fingerprint.

Cite this