{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,14]],"date-time":"2026-03-14T21:36:52Z","timestamp":1773524212846,"version":"3.50.1"},"reference-count":17,"publisher":"Association for Computing Machinery (ACM)","issue":"12","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2015,8]]},"abstract":"<jats:p>\n            Numerous applications continuously produce big amounts of data series, and in several time critical scenarios analysts need to be able to query these data as soon as they become available. An adaptive index data structure, ADS+, which is specifically tailored to solve the problem of indexing and querying very large data series collections has been recently proposed as a solution to this problem. The main idea is that instead of building the complete index over the complete data set up-front and querying only later, we interactively and adaptively build parts of the index, only for the parts of the data on which the users pose queries. The net effect is that instead of waiting for extended periods of time for the index creation, users can immediately start exploring the data series. In this work, we present a demonstration of ADS+; we introduce RINSE, a system that allows users to experience the benefits of the ADS+ adaptive index through an intuitive web interface. Users can explore large datasets and find patterns of interest, using nearest neighbor search. They can draw queries (data series) using a mouse, or touch screen, or they can select from a predefined list of data series. RINSE can scale to large data sizes, while drastically reducing the data to query delay: by the time state-of-the-art indexing techniques finish indexing 1 billion data series (and before answering even a single query), adaptive data series indexing can already answer 3 * 10\n            <jats:sup>5<\/jats:sup>\n            queries.\n          <\/jats:p>","DOI":"10.14778\/2824032.2824099","type":"journal-article","created":{"date-parts":[[2015,9,16]],"date-time":"2015-09-16T12:18:17Z","timestamp":1442405897000},"page":"1912-1915","source":"Crossref","is-referenced-by-count":29,"title":["RINSE"],"prefix":"10.14778","volume":"8","author":[{"given":"Kostas","family":"Zoumpatianos","sequence":"first","affiliation":[{"name":"University of Trento"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Stratos","family":"Idreos","sequence":"additional","affiliation":[{"name":"Harvard University"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Themis","family":"Palpanas","sequence":"additional","affiliation":[{"name":"Paris Descartes University"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"320","published-online":{"date-parts":[[2015,8]]},"reference":[{"key":"e_1_2_1_1_1","volume-title":"FODO","author":"Agrawal R.","year":"1993","unstructured":"R. Agrawal , C. Faloutsos , and A. N. Swami . Efficient similarity search in sequence databases . In FODO , 1993 . R. Agrawal, C. Faloutsos, and A. N. Swami. Efficient similarity search in sequence databases. In FODO, 1993."},{"key":"e_1_2_1_2_1","volume-title":"VLDB","author":"Berchtold S.","year":"1996","unstructured":"S. Berchtold , D. A. Keim , and H.-P. Kriegel . The X-tree : An index structure for high-dimensional data . In VLDB , 1996 . S. Berchtold, D. A. Keim, and H.-P. Kriegel. The X-tree: An index structure for high-dimensional data. In VLDB, 1996."},{"key":"e_1_2_1_3_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2010.124"},{"issue":"1","key":"e_1_2_1_4_1","first-page":"123","article-title":"Beyond One Billion Time Series: Indexing and Mining Very Large Time Series Collections with iSAX2+","volume":"39","author":"Camerra A.","year":"2014","unstructured":"A. Camerra , J. Shieh , T. Palpanas , T. Rakthanmanon , and E. Keogh . Beyond One Billion Time Series: Indexing and Mining Very Large Time Series Collections with iSAX2+ . KAIS , 39 ( 1 ): 123 -- 151 , 2014 . A. Camerra, J. Shieh, T. Palpanas, T. Rakthanmanon, and E. Keogh. Beyond One Billion Time Series: Indexing and Mining Very Large Time Series Collections with iSAX2+. KAIS, 39(1):123--151, 2014.","journal-title":"KAIS"},{"key":"e_1_2_1_5_1","volume-title":"ICDE","author":"Chan K.-P.","year":"1999","unstructured":"K.-P. Chan and A.-C. Fu . Efficient time series matching by wavelets . In ICDE , 1999 . K.-P. Chan and A.-C. Fu. Efficient time series matching by wavelets. In ICDE, 1999."},{"key":"e_1_2_1_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/602259.602266"},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.14778\/2168651.2168652"},{"key":"e_1_2_1_9_1","volume-title":"CIDR","author":"Idreos S.","year":"2011","unstructured":"S. Idreos , I. Alagiannis , R. Johnson , and A. Ailamaki . Here are my Data Files. Here are my Queries. Where are my Results ? In CIDR , 2011 . S. Idreos, I. Alagiannis, R. Johnson, and A. Ailamaki. Here are my Data Files. Here are my Queries. Where are my Results? In CIDR, 2011."},{"key":"e_1_2_1_10_1","volume-title":"CIDR","author":"Idreos S.","year":"2013","unstructured":"S. Idreos and E. Liarou . dbtouch: Analytics at your fingertips . In CIDR , 2013 . S. Idreos and E. Liarou. dbtouch: Analytics at your fingertips. In CIDR, 2013."},{"key":"e_1_2_1_11_1","doi-asserted-by":"publisher","DOI":"10.14778\/2002938.2002944"},{"key":"e_1_2_1_12_1","volume-title":"SIGMOD","author":"Idreos S.","year":"2015","unstructured":"S. Idreos , O. Papaemmanouil , and S. Chaudhuri . Overview of Data Exploration Techniques . In SIGMOD , Tutorial , 2015 . 10.1145\/2723372.2731084 S. Idreos, O. Papaemmanouil, and S. Chaudhuri. Overview of Data Exploration Techniques. In SIGMOD, Tutorial, 2015. 10.1145\/2723372.2731084"},{"issue":"3","key":"e_1_2_1_13_1","first-page":"263","article-title":"Dimensionality reduction for fast similarity search in large time series databases","volume":"3","author":"Keogh E.","year":"2000","unstructured":"E. Keogh , K. Chakrabarti , and M. Pazzani . Dimensionality reduction for fast similarity search in large time series databases . KAIS , 3 ( 3 ): 263 -- 286 , 2000 . E. Keogh, K. Chakrabarti, and M. Pazzani. Dimensionality reduction for fast similarity search in large time series databases. KAIS, 3(3):263--286, 2000.","journal-title":"KAIS"},{"key":"e_1_2_1_14_1","volume-title":"DMKD Workshop, 2003","author":"Lin J.","year":"2082","unstructured":"J. Lin , E. Keogh , and S. Lonardi . A symbolic representation of time series, with implications for streaming algorithms . In DMKD Workshop, 2003 . 10.1145\/88 2082 .882086 J. Lin, E. Keogh, and S. Lonardi. A symbolic representation of time series, with implications for streaming algorithms. In DMKD Workshop, 2003. 10.1145\/882082.882086"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1401890.1401966"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.14778\/2536206.2536208"},{"key":"e_1_2_1_17_1","volume-title":"SIGMOD","author":"Zoumpatianos K.","year":"2014","unstructured":"K. Zoumpatianos , S. Idreos , and T. Palpanas . Indexing for interactive exploration of big data series . In SIGMOD , 2014 . 10.1145\/2588555.2610498 K. Zoumpatianos, S. Idreos, and T. Palpanas. Indexing for interactive exploration of big data series. In SIGMOD, 2014. 10.1145\/2588555.2610498"},{"key":"e_1_2_1_18_1","volume-title":"SIGKDD","author":"Zoumpatianos K.","year":"2015","unstructured":"K. Zoumpatianos , Y. Lou , T. Palpanas , and J. Gehrke . Query workloads for data series indexes . In SIGKDD , 2015 . 10.1145\/2783258.2783382 K. Zoumpatianos, Y. Lou, T. Palpanas, and J. Gehrke. Query workloads for data series indexes. In SIGKDD, 2015. 10.1145\/2783258.2783382"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/2824032.2824099","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:21:11Z","timestamp":1672222871000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/2824032.2824099"}},"subtitle":["interactive data series exploration with ADS+"],"short-title":[],"issued":{"date-parts":[[2015,8]]},"references-count":17,"journal-issue":{"issue":"12","published-print":{"date-parts":[[2015,8]]}},"alternative-id":["10.14778\/2824032.2824099"],"URL":"https:\/\/doi.org\/10.14778\/2824032.2824099","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2015,8]]}}}