SENSOR: Data-driven Construction of Sketch-based Visual Query Interfaces for Time Series Data

Li Yan, Nerissa Xu, Guozhong Li, Sourav S Bhowmick, Byron Choi, Jianliang Xu

Research output: Contribution to journalConference articlepeer-review

1 Citation (Scopus)

Abstract

Sketching is a common approach to visually query time series data. However, a recent study reported that sketching a pattern for querying is “often ineffective on its own” in practice due to lack of “representative objects” to facilitate bottom-up search. In this demonstration, we present a novel data-driven sketch-based visual query interface (VQI) construction system called sensor to alleviate this challenge. Given a time series dataset, sensor automatically constructs its VQI by populating different components from the underlying data. Specifically, it discovers and exposes a set of representative objects in the form of VST-aware shapelets to facilitate query formulation. Such data-driven construction has several potential benefits such as empowering efficient top-down and bottom-up search and portability of the interface across different application domains and sources.

Original languageEnglish
Pages (from-to)3650-3653
Number of pages4
JournalProceedings of the VLDB Endowment
Volume15
Issue number12
DOIs
Publication statusPublished - Aug 2022
Event48th International Conference on Very Large Data Bases, VLDB 2022 - Sydney, Australia
Duration: 5 Sept 20229 Sept 2022

Scopus Subject Areas

  • Computer Science (miscellaneous)
  • Computer Science(all)

Fingerprint

Dive into the research topics of 'SENSOR: Data-driven Construction of Sketch-based Visual Query Interfaces for Time Series Data'. Together they form a unique fingerprint.

Cite this