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 language | English |
|---|---|
| Pages (from-to) | 3650-3653 |
| Number of pages | 4 |
| Journal | Proceedings of the VLDB Endowment |
| Volume | 15 |
| Issue number | 12 |
| DOIs | |
| Publication status | Published - Aug 2022 |
| Event | 48th International Conference on Very Large Data Bases, VLDB 2022 - Sydney, Australia Duration: 5 Sept 2022 → 9 Sept 2022 |
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