{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,8,18]],"date-time":"2026-08-18T03:06:10Z","timestamp":1787022370938,"version":"build-2736575974"},"reference-count":13,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2022,8]]},"abstract":"<jats:p>\n                    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\n                    <jats:italic>bottom-up search.<\/jats:italic>\n                    In this demonstration, we present a novel\n                    <jats:italic>data-driven<\/jats:italic>\n                    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\n                    <jats:italic>VST-aware shapelets<\/jats:italic>\n                    to facilitate query formulation. Such data-driven construction has several potential benefits such as empowering efficient\n                    <jats:italic>top-down<\/jats:italic>\n                    and\n                    <jats:italic>bottom-up<\/jats:italic>\n                    search and portability of the interface across different application domains and sources.\n                  <\/jats:p>","DOI":"10.14778\/3554821.3554866","type":"journal-article","created":{"date-parts":[[2022,9,29]],"date-time":"2022-09-29T18:28:39Z","timestamp":1664476119000},"page":"3650-3653","source":"Crossref","is-referenced-by-count":8,"title":["SENSOR"],"prefix":"10.14778","volume":"15","author":[{"given":"Li","family":"Yan","sequence":"first","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Nerissa","family":"Xu","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Guozhong","family":"Li","sequence":"additional","affiliation":[{"name":"Hong Kong Baptist University, Hong Kong SAR"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sourav S","family":"Bhowmick","sequence":"additional","affiliation":[{"name":"Nanyang Technological University, Singapore"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Byron","family":"Choi","sequence":"additional","affiliation":[{"name":"Hong Kong Baptist University, Hong Kong SAR"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jianliang","family":"Xu","sequence":"additional","affiliation":[{"name":"Hong Kong Baptist University, Hong Kong SAR"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2022,9,29]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.is.2015.04.007"},{"key":"e_1_2_1_2_1","doi-asserted-by":"publisher","DOI":"10.1145\/3514221.3522562"},{"key":"e_1_2_1_3_1","volume-title":"Last accessed 20th","author":"Chen Y.","year":"2022","unstructured":"Y. Chen , The UCR time series classification archive. https:\/\/www.cs.ucr.edu\/~eamonn\/time_series_data_2018\/ , Last accessed 20th June , 2022 . Y. Chen, et al. The UCR time series classification archive. https:\/\/www.cs.ucr.edu\/~eamonn\/time_series_data_2018\/, Last accessed 20th June, 2022."},{"key":"e_1_2_1_4_1","volume-title":"The Semantics of Sketch: Flexibility in Visual Query Systems for Time Series Data. In 2016 IEEE Conference on Visual Analytics Science and Technology (VAST), 131--140","author":"Correl M.","year":"2016","unstructured":"M. Correl , M. Gleicher . The Semantics of Sketch: Flexibility in Visual Query Systems for Time Series Data. In 2016 IEEE Conference on Visual Analytics Science and Technology (VAST), 131--140 , IEEE CS, 2016 . M. Correl, M. Gleicher. The Semantics of Sketch: Flexibility in Visual Query Systems for Time Series Data. In 2016 IEEE Conference on Visual Analytics Science and Technology (VAST), 131--140, IEEE CS, 2016."},{"key":"e_1_2_1_5_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-4471-2804-5_17"},{"key":"e_1_2_1_6_1","volume-title":"Dimensionality reduction for fast similarity search in large time series databases. Knowledge and information Systems 3(3), 263--286","author":"Keogh E.","year":"2001","unstructured":"E. Keogh , K. Chakrabarti , M. Pazzani , S. Mehrotra . Dimensionality reduction for fast similarity search in large time series databases. Knowledge and information Systems 3(3), 263--286 , Springer , 2001 . E. Keogh, K. Chakrabarti, M. Pazzani, S. Mehrotra. Dimensionality reduction for fast similarity search in large time series databases. Knowledge and information Systems 3(3), 263--286, Springer, 2001."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1109\/TVCG.2020.3002950"},{"issue":"1","key":"e_1_2_1_8_1","first-page":"1267","article-title":"You Can't Always Sketch What you Want","volume":"26","author":"Lee J.L.","year":"2020","unstructured":"D. J.L. Lee , You Can't Always Sketch What you Want : Understanding Sense-making in Visual Query Systems. IEEE Trans. Vis. Comput. Graph. , 26 ( 1 ): 1267 -- 1277 , IEEE CS, 2020 . D.J.L. Lee, et al. You Can't Always Sketch What you Want: Understanding Sense-making in Visual Query Systems. IEEE Trans. Vis. Comput. Graph., 26(1): 1267--1277, IEEE CS, 2020.","journal-title":"Understanding Sense-making in Visual Query Systems. IEEE Trans. Vis. Comput. Graph."},{"key":"e_1_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2020.2995870"},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/882082.882086"},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.1145\/3173574.3173962"},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.14778\/3025111.3025126"},{"key":"e_1_2_1_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557122"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3554821.3554866","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T06:32:55Z","timestamp":1672209175000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3554821.3554866"}},"subtitle":["data-driven construction of sketch-based visual query interfaces for time series data"],"short-title":[],"issued":{"date-parts":[[2022,8]]},"references-count":13,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2022,8]]}},"alternative-id":["10.14778\/3554821.3554866"],"URL":"https:\/\/doi.org\/10.14778\/3554821.3554866","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2022,8]]}}}