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Qetch: Time Series Querying with Expressive Sketches

Published:27 May 2018Publication History

ABSTRACT

Query-by-sketch tools allow users to sketch a pattern to search a time series database for matches. Prior work adopts a bottom-up design approach: the sketching interface is built to reflect the inner workings of popular matching algorithms like Dynamic time warping (DTW) or Euclidean distance (ED). We design Qetch, a query-by-sketch tool for time series data, top-down. Users freely sketch patterns on a scale-less canvas. By studying how humans sketch time series patterns we develop a matching algorithm that accounts for human sketching errors. Qetch's top-down design and novel matching algorithm enable the easy construction of expressive queries that include regular expressions over sketches and queries over multiple time series. Our demonstration showcases Qetch and summarizes results from our evaluation of Qetch's effectiveness.

References

  1. P. Cortez, M. Rio, M. Rocha, and P. Sousa. 2006. Internet Traffic Forecasting using Neural Networks The 2006 IEEE International Joint Conference on Neural Network Proceedings. 2635--2642. /10.1145/634067.634292Google ScholarGoogle Scholar
  2. Kostas Zoumpatianos, Stratos Idreos, and Themis Palpanas. 2015. RINSE: Interactive Data Series Exploration with ADS. Proc. VLDB Endow., Vol. 8, 12 (Aug.. 2015), 1912--1915. showISSN2150--8097 Google ScholarGoogle ScholarDigital LibraryDigital Library

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  1. Qetch: Time Series Querying with Expressive Sketches

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        cover image ACM Conferences
        SIGMOD '18: Proceedings of the 2018 International Conference on Management of Data
        May 2018
        1874 pages
        ISBN:9781450347037
        DOI:10.1145/3183713

        Copyright © 2018 ACM

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        Association for Computing Machinery

        New York, NY, United States

        Publication History

        • Published: 27 May 2018

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        Acceptance Rates

        SIGMOD '18 Paper Acceptance Rate90of461submissions,20%Overall Acceptance Rate785of4,003submissions,20%

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