{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,30]],"date-time":"2026-09-30T22:42:49Z","timestamp":1790808169682,"version":"4.1.0"},"reference-count":103,"publisher":"Association for Computing Machinery (ACM)","issue":"8","content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2023,4]]},"abstract":"<jats:p>Similarity search is a core analytical task, and its performance critically depends on the choice of distance measure. For time-series querying, elastic measures achieve state-of-the-art accuracy but are computationally expensive. Thus, fast lower bounding (LB) measures prune unnecessary comparisons with elastic distances to accelerate similarity search. Despite decades of attention, there has never been a study to assess the progress in this area. In addition, the research has disproportionately focused on one popular elastic measure, while other accurate measures have received little or no attention. Therefore, there is merit in developing a framework to accumulate knowledge from previously developed LBs and eliminate the notoriously challenging task of designing separate LBs for each elastic measure. In this paper, we perform the first comprehensive study of 11 LBs spanning 5 elastic measures using 128 datasets. We identify four properties that constitute the effectiveness of LBs and propose the Generalized Lower Bounding (GLB) framework to satisfy all desirable properties. GLB creates cache-friendly summaries, adaptively exploits summaries of both query and target time series, and captures boundary distances in an unsupervised manner. GLB outperforms<jats:italic>all<\/jats:italic>LBs in speedup (e.g., up to 13.5\u00d7 faster against the strongest LB in terms of pruning power), establishes new state-of-the-art results for the 5 elastic measures, and provides the first LBs for 2 elastic measures with no known LBs. Overall, GLB enables the effective development of LBs to facilitate fast similarity search.<\/jats:p>","DOI":"10.14778\/3594512.3594530","type":"journal-article","created":{"date-parts":[[2023,6,23]],"date-time":"2023-06-23T00:28:36Z","timestamp":1687480116000},"page":"2019-2032","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":23,"title":["Accelerating Similarity Search for Elastic Measures: A Study and New Generalization of Lower Bounding Distances"],"prefix":"10.14778","volume":"16","author":[{"given":"John","family":"Paparrizos","sequence":"first","affiliation":[{"name":"The Ohio State University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Kaize","family":"Wu","sequence":"additional","affiliation":[{"name":"University of Chicago"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Aaron","family":"Elmore","sequence":"additional","affiliation":[{"name":"University of Chicago"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Christos","family":"Faloutsos","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Michael J.","family":"Franklin","sequence":"additional","affiliation":[{"name":"University of Chicago"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"320","published-online":{"date-parts":[[2023,6,22]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"crossref","unstructured":"Jonathan Alon Stan Sclaroff George Kollios and Vladimir Pavlovic. 2003. Discovering clusters in motion time-series data. In CVPR. 375--381. Jonathan Alon Stan Sclaroff George Kollios and Vladimir Pavlovic. 2003. Discovering clusters in motion time-series data. In CVPR. 375--381.","DOI":"10.1109\/CVPR.2003.1211378"},{"key":"e_1_2_1_2_1","unstructured":"George Amvrosiadis Ali R Butt Vasily Tarasov Erez Zadok Ming Zhao Irfan Ahmad Remzi H Arpaci-Dusseau Feng Chen Yiran Chen Yong Chen etal 2018. Data Storage Research Vision 2025: Report on NSF Visioning Workshop held May 30--June 1 2018. (2018). George Amvrosiadis Ali R Butt Vasily Tarasov Erez Zadok Ming Zhao Irfan Ahmad Remzi H Arpaci-Dusseau Feng Chen Yiran Chen Yong Chen et al. 2018. Data Storage Research Vision 2025: Report on NSF Visioning Workshop held May 30--June 1 2018. (2018)."},{"key":"e_1_2_1_3_1","volume-title":"International Conference on Extending Database Technology. Springer, 276--294","author":"A\u00dffalg Johannes","year":"2006","unstructured":"Johannes A\u00dffalg , Hans-Peter Kriegel , Peer Kr\u00f6ger , Peter Kunath , Alexey Pryakhin , and Matthias Renz . 2006 . Similarity search on time series based on threshold queries . In International Conference on Extending Database Technology. Springer, 276--294 . Johannes A\u00dffalg, Hans-Peter Kriegel, Peer Kr\u00f6ger, Peter Kunath, Alexey Pryakhin, and Matthias Renz. 2006. Similarity search on time series based on threshold queries. In International Conference on Extending Database Technology. Springer, 276--294."},{"key":"e_1_2_1_4_1","doi-asserted-by":"crossref","first-page":"606","DOI":"10.1007\/s10618-016-0483-9","article-title":"The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances","volume":"31","author":"Bagnall Anthony","year":"2017","unstructured":"Anthony Bagnall , Jason Lines , Aaron Bostrom , James Large , and Eamonn Keogh . 2017 . The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances . Data Mining and Knowledge Discovery 31 , 3 (2017), 606 -- 660 . Anthony Bagnall, Jason Lines, Aaron Bostrom, James Large, and Eamonn Keogh. 2017. The great time series classification bake off: a review and experimental evaluation of recent algorithmic advances. Data Mining and Knowledge Discovery 31, 3 (2017), 606--660.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"e_1_2_1_5_1","doi-asserted-by":"crossref","unstructured":"Anthony J Bagnall and Gareth J Janacek. 2004. Clustering time series from ARMA models with clipped data. In KDD. 49--58. Anthony J Bagnall and Gareth J Janacek. 2004. Clustering time series from ARMA models with clipped data. In KDD. 49--58.","DOI":"10.1145\/1014052.1014061"},{"key":"e_1_2_1_6_1","volume-title":"k-shapestream: Probabilistic streaming clustering for electric grid events. In 2021 IEEE Madrid PowerTech","author":"Bariya Mohini","unstructured":"Mohini Bariya , Alexandra von Meier , John Paparrizos , and Michael J Franklin . 2021. k-shapestream: Probabilistic streaming clustering for electric grid events. In 2021 IEEE Madrid PowerTech . IEEE , 1--6. Mohini Bariya, Alexandra von Meier, John Paparrizos, and Michael J Franklin. 2021. k-shapestream: Probabilistic streaming clustering for electric grid events. In 2021 IEEE Madrid PowerTech. IEEE, 1--6."},{"key":"e_1_2_1_7_1","doi-asserted-by":"crossref","first-page":"149","DOI":"10.14778\/2735471.2735476","article-title":"Rare time series motif discovery from unbounded streams","volume":"8","author":"Begum Nurjahan","year":"2014","unstructured":"Nurjahan Begum and Eamonn Keogh . 2014 . Rare time series motif discovery from unbounded streams . Proceedings of the VLDB Endowment 8 , 2 (2014), 149 -- 160 . Nurjahan Begum and Eamonn Keogh. 2014. Rare time series motif discovery from unbounded streams. Proceedings of the VLDB Endowment 8, 2 (2014), 149--160.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_8_1","volume-title":"AAAI Workshop on KDD. 359--370","author":"Berndt Donald J","year":"1994","unstructured":"Donald J Berndt and James Clifford . 1994 . Using Dynamic Time Warping to Find Patterns in Time Series .. In AAAI Workshop on KDD. 359--370 . Donald J Berndt and James Clifford. 1994. Using Dynamic Time Warping to Find Patterns in Time Series.. In AAAI Workshop on KDD. 359--370."},{"key":"e_1_2_1_9_1","volume-title":"Unsupervised and scalable subsequence anomaly detection in large data series. The VLDB Journal","author":"Boniol Paul","year":"2021","unstructured":"Paul Boniol , Michele Linardi , Federico Roncallo , Themis Palpanas , Mohammed Meftah , and Emmanuel Remy . 2021. Unsupervised and scalable subsequence anomaly detection in large data series. The VLDB Journal ( 2021 ), 1--23. Paul Boniol, Michele Linardi, Federico Roncallo, Themis Palpanas, Mohammed Meftah, and Emmanuel Remy. 2021. Unsupervised and scalable subsequence anomaly detection in large data series. 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Proceedings of the VLDB Endowment 14, 12 (2021), 2867--2870.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_14_1","doi-asserted-by":"crossref","first-page":"1717","DOI":"10.14778\/3467861.3467863","article-title":"SAND: streaming subsequence anomaly detection","volume":"14","author":"Boniol Paul","year":"2021","unstructured":"Paul Boniol , John Paparrizos , Themis Palpanas , and Michael J Franklin . 2021 . SAND: streaming subsequence anomaly detection . Proceedings of the VLDB Endowment 14 , 10 (2021), 1717 -- 1729 . Paul Boniol, John Paparrizos, Themis Palpanas, and Michael J Franklin. 2021. SAND: streaming subsequence anomaly detection. Proceedings of the VLDB Endowment 14, 10 (2021), 1717--1729.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_15_1","volume-title":"ACM sigmod record","author":"Breunig Markus M","unstructured":"Markus M Breunig , Hans-Peter Kriegel , Raymond T Ng , and J\u00f6rg Sander . 2000. LOF: identifying density-based local outliers . In ACM sigmod record , Vol. 29 . ACM , 93--104. Markus M Breunig, Hans-Peter Kriegel, Raymond T Ng, and J\u00f6rg Sander. 2000. LOF: identifying density-based local outliers. In ACM sigmod record, Vol. 29. ACM, 93--104."},{"key":"e_1_2_1_16_1","first-page":"186","article-title":"Clustering-Based Similarity Search in Metric Spaces with Sparse Spatial Centers. Proc. 34th Int'l Conf","volume":"4910","author":"Brisaboa N.","year":"2008","unstructured":"N. Brisaboa , O. Pedreira , D. Seco R. Solar , and R. Uribe . 2008 . Clustering-Based Similarity Search in Metric Spaces with Sparse Spatial Centers. Proc. 34th Int'l Conf . Current Trends in Theory and Practice of Computer Science 4910 (2008), 186 -- 197 . N. Brisaboa, O. Pedreira, D. Seco R. Solar, and R. Uribe. 2008. Clustering-Based Similarity Search in Metric Spaces with Sparse Spatial Centers. Proc. 34th Int'l Conf. Current Trends in Theory and Practice of Computer Science 4910 (2008), 186--197.","journal-title":"Current Trends in Theory and Practice of Computer Science"},{"key":"e_1_2_1_17_1","doi-asserted-by":"crossref","unstructured":"Yuhan Cai and Raymond Ng. 2004. Indexing spatio-temporal trajectories with Chebyshev polynomials. In SIGMOD. 599--610. Yuhan Cai and Raymond Ng. 2004. Indexing spatio-temporal trajectories with Chebyshev polynomials. In SIGMOD. 599--610.","DOI":"10.1145\/1007568.1007636"},{"key":"e_1_2_1_18_1","volume-title":"2010 IEEE International Conference on Data Mining. IEEE, 58--67","author":"Camerra Alessandro","year":"2010","unstructured":"Alessandro Camerra , Themis Palpanas , Jin Shieh , and Eamonn Keogh . 2010 . iSAX 2.0: Indexing and mining one billion time series . In 2010 IEEE International Conference on Data Mining. IEEE, 58--67 . Alessandro Camerra, Themis Palpanas, Jin Shieh, and Eamonn Keogh. 2010. iSAX 2.0: Indexing and mining one billion time series. In 2010 IEEE International Conference on Data Mining. IEEE, 58--67."},{"key":"e_1_2_1_19_1","doi-asserted-by":"crossref","unstructured":"Lei Chen and Raymond Ng. 2004. On the marriage of Lp-norms and edit distance. In VLDB. 792--803. Lei Chen and Raymond Ng. 2004. On the marriage of Lp-norms and edit distance. In VLDB. 792--803.","DOI":"10.1016\/B978-012088469-8.50070-X"},{"key":"e_1_2_1_20_1","doi-asserted-by":"crossref","unstructured":"Lei Chen M Tamer \u00d6zsu and Vincent Oria. 2005. Robust and fast similarity search for moving object trajectories. In SIGMOD. 491--502. Lei Chen M Tamer \u00d6zsu and Vincent Oria. 2005. Robust and fast similarity search for moving object trajectories. In SIGMOD. 491--502.","DOI":"10.1145\/1066157.1066213"},{"key":"e_1_2_1_21_1","unstructured":"Qiuxia Chen Lei Chen Xiang Lian Yunhao Liu and Jeffrey Xu Yu. 2007. Indexable PLA for efficient similarity search. In VLDB. 435--446. Qiuxia Chen Lei Chen Xiang Lian Yunhao Liu and Jeffrey Xu Yu. 2007. Indexable PLA for efficient similarity search. In VLDB. 435--446."},{"key":"e_1_2_1_22_1","volume-title":"Beng Chin Ooi, and Anthony KH Tung","author":"Chen Yueguo","year":"2007","unstructured":"Yueguo Chen , Mario A Nascimento , Beng Chin Ooi, and Anthony KH Tung . 2007 . Spade : On shape-based pattern detection in streaming time series. In ICDE. 786--795. Yueguo Chen, Mario A Nascimento, Beng Chin Ooi, and Anthony KH Tung. 2007. Spade: On shape-based pattern detection in streaming time series. In ICDE. 786--795."},{"key":"e_1_2_1_23_1","volume-title":"Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 493--498","author":"Chiu Bill","year":"2003","unstructured":"Bill Chiu , Eamonn Keogh , and Stefano Lonardi . 2003 . Probabilistic discovery of time series motifs . In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 493--498 . Bill Chiu, Eamonn Keogh, and Stefano Lonardi. 2003. Probabilistic discovery of time series motifs. In Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 493--498."},{"key":"e_1_2_1_24_1","volume-title":"Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining. ACM, 743--749","author":"Cole Richard","year":"2005","unstructured":"Richard Cole , Dennis Shasha , and Xiaojian Zhao . 2005 . Fast window correlations over uncooperative time series . In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining. ACM, 743--749 . Richard Cole, Dennis Shasha, and Xiaojian Zhao. 2005. Fast window correlations over uncooperative time series. In Proceedings of the eleventh ACM SIGKDD international conference on Knowledge discovery in data mining. ACM, 743--749."},{"key":"e_1_2_1_25_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/1348246.1348248","article-title":"Image retrieval: Ideas, influences, and trends of the new age","volume":"40","author":"Datta Ritendra","year":"2008","unstructured":"Ritendra Datta , Dhiraj Joshi , Jia Li , and James Z Wang . 2008 . Image retrieval: Ideas, influences, and trends of the new age . ACM Computing Surveys (Csur) 40 , 2 (2008), 1 -- 60 . Ritendra Datta, Dhiraj Joshi, Jia Li, and James Z Wang. 2008. Image retrieval: Ideas, influences, and trends of the new age. ACM Computing Surveys (Csur) 40, 2 (2008), 1--60.","journal-title":"ACM Computing Surveys (Csur)"},{"key":"e_1_2_1_26_1","doi-asserted-by":"crossref","unstructured":"H. A. Dau E. Keogh K. Kamgar C.-C. M. Yeh Y. Zhu S. Gharghabi C. A. Ratanamahatana Yanping B. Hu N. Begum A. Bagnall A. Mueen and G. Batista. [n.d.]. The ucr time series classification archive. https:\/\/www.cs.ucr.edu\/~eamonn\/time_series_data_2018\/ H. A. Dau E. Keogh K. Kamgar C.-C. M. Yeh Y. Zhu S. Gharghabi C. A. Ratanamahatana Yanping B. Hu N. Begum A. Bagnall A. Mueen and G. Batista. [n.d.]. The ucr time series classification archive. https:\/\/www.cs.ucr.edu\/~eamonn\/time_series_data_2018\/","DOI":"10.1109\/JAS.2019.1911747"},{"key":"e_1_2_1_27_1","doi-asserted-by":"crossref","first-page":"1542","DOI":"10.14778\/1454159.1454226","article-title":"Querying and mining of time series data: experimental comparison of representations and distance measures","volume":"1","author":"Ding Hui","year":"2008","unstructured":"Hui Ding , Goce Trajcevski , Peter Scheuermann , Xiaoyue Wang , and Eamonn Keogh . 2008 . Querying and mining of time series data: experimental comparison of representations and distance measures . Proceedings of the VLDB Endowment 1 , 2 (2008), 1542 -- 1552 . Hui Ding, Goce Trajcevski, Peter Scheuermann, Xiaoyue Wang, and Eamonn Keogh. 2008. Querying and mining of time series data: experimental comparison of representations and distance measures. Proceedings of the VLDB Endowment 1, 2 (2008), 1542--1552.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_28_1","doi-asserted-by":"crossref","first-page":"473","DOI":"10.14778\/2735479.2735481","article-title":"Yading: Fast clustering of large-scale time series data","volume":"8","author":"Ding Rui","year":"2015","unstructured":"Rui Ding , Qiang Wang , Yingnong Dang , Qiang Fu , Haidong Zhang , and Dongmei Zhang . 2015 . Yading: Fast clustering of large-scale time series data . Proceedings of the VLDB Endowment 8 , 5 (2015), 473 -- 484 . Rui Ding, Qiang Wang, Yingnong Dang, Qiang Fu, Haidong Zhang, and Dongmei Zhang. 2015. Yading: Fast clustering of large-scale time series data. Proceedings of the VLDB Endowment 8, 5 (2015), 473--484.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_29_1","volume-title":"International Conference on Machine Learning. PMLR, 1745--1754","author":"Dziedzic Adam","year":"2019","unstructured":"Adam Dziedzic , John Paparrizos , Sanjay Krishnan , Aaron Elmore , and Michael Franklin . 2019 . Band-limited training and inference for convolutional neural networks . In International Conference on Machine Learning. PMLR, 1745--1754 . Adam Dziedzic, John Paparrizos, Sanjay Krishnan, Aaron Elmore, and Michael Franklin. 2019. Band-limited training and inference for convolutional neural networks. In International Conference on Machine Learning. PMLR, 1745--1754."},{"key":"e_1_2_1_30_1","doi-asserted-by":"crossref","first-page":"112","DOI":"10.14778\/3282495.3282498","article-title":"The lernaean hydra of data series similarity search: An experimental evaluation of the state of the art","volume":"12","author":"Echihabi Karima","year":"2018","unstructured":"Karima Echihabi , Kostas Zoumpatianos , Themis Palpanas , and Houda Benbrahim . 2018 . The lernaean hydra of data series similarity search: An experimental evaluation of the state of the art . Proceedings of the VLDB Endowment 12 , 2 (2018), 112 -- 127 . Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas, and Houda Benbrahim. 2018. The lernaean hydra of data series similarity search: An experimental evaluation of the state of the art. Proceedings of the VLDB Endowment 12, 2 (2018), 112--127.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_31_1","doi-asserted-by":"crossref","first-page":"403","DOI":"10.14778\/3368289.3368303","article-title":"Return of the Lernaean Hydra: experimental evaluation of data series approximate similarity search","volume":"13","author":"Echihabi Karima","year":"2019","unstructured":"Karima Echihabi , Kostas Zoumpatianos , Themis Palpanas , and Houda Benbrahim . 2019 . Return of the Lernaean Hydra: experimental evaluation of data series approximate similarity search . Proceedings of the VLDB Endowment 13 , 3 (2019), 403 -- 420 . Karima Echihabi, Kostas Zoumpatianos, Themis Palpanas, and Houda Benbrahim. 2019. Return of the Lernaean Hydra: experimental evaluation of data series approximate similarity search. Proceedings of the VLDB Endowment 13, 3 (2019), 403--420.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_32_1","doi-asserted-by":"crossref","unstructured":"Christos Faloutsos M. Ranganathan and Yannis Manolopoulos. 1994. Fast Subsequence Matching in Time-series Databases. In SIGMOD. 419--429. Christos Faloutsos M. Ranganathan and Yannis Manolopoulos. 1994. Fast Subsequence Matching in Time-series Databases. In SIGMOD. 419--429.","DOI":"10.1145\/191843.191925"},{"key":"e_1_2_1_33_1","doi-asserted-by":"crossref","unstructured":"Elias Frentzos Kostas Gratsias and Yannis Theodoridis. 2007. Index-based most similar trajectory search. In ICDE. 816--825. Elias Frentzos Kostas Gratsias and Yannis Theodoridis. 2007. Index-based most similar trajectory search. In ICDE. 816--825.","DOI":"10.1109\/ICDE.2007.367927"},{"key":"e_1_2_1_34_1","volume-title":"Proc. IEEE Int'l Conf. Data Eng. (ICDE)","author":"Ganti V.","year":"1999","unstructured":"V. Ganti , R. Ramakrishnan , J. Gehrke , A.L. Powell , and J.C. French . 1999. Clustering Large Data Sets in Arbitrary Metric Spaces . Proc. IEEE Int'l Conf. Data Eng. (ICDE) ( 1999 ), 502--511. V. Ganti, R. Ramakrishnan, J. Gehrke, A.L. Powell, and J.C. French. 1999. Clustering Large Data Sets in Arbitrary Metric Spaces. Proc. IEEE Int'l Conf. Data Eng. (ICDE) (1999), 502--511."},{"key":"e_1_2_1_35_1","volume-title":"Social Informatics: 8th International Conference, SocInfo 2016, Bellevue, WA, USA, November 11--14, 2016, Proceedings, Part I 8. Springer, 41--57","author":"Goel Rahul","year":"2016","unstructured":"Rahul Goel , Sandeep Soni , Naman Goyal , John Paparrizos , Hanna Wallach , Fernando Diaz , and Jacob Eisenstein . 2016 . The social dynamics of language change in online networks . In Social Informatics: 8th International Conference, SocInfo 2016, Bellevue, WA, USA, November 11--14, 2016, Proceedings, Part I 8. Springer, 41--57 . Rahul Goel, Sandeep Soni, Naman Goyal, John Paparrizos, Hanna Wallach, Fernando Diaz, and Jacob Eisenstein. 2016. The social dynamics of language change in online networks. In Social Informatics: 8th International Conference, SocInfo 2016, Bellevue, WA, USA, November 11--14, 2016, Proceedings, Part I 8. Springer, 41--57."},{"key":"e_1_2_1_36_1","doi-asserted-by":"crossref","first-page":"43","DOI":"10.1109\/TASSP.1978.1163055","article-title":"Dynamic programming algorithm optimization for spoken word recognition","volume":"26","author":"Sakoe","year":"1978","unstructured":"Sakoe H and Chiba S. 1978 . Dynamic programming algorithm optimization for spoken word recognition . IEEE Trans Acoust, Speech, Signal Process 26 , 1 (1978), 43 -- 49 . Sakoe H and Chiba S. 1978. Dynamic programming algorithm optimization for spoken word recognition. IEEE Trans Acoust, Speech, Signal Process 26, 1 (1978), 43--49.","journal-title":"IEEE Trans Acoust, Speech, Signal Process"},{"key":"e_1_2_1_37_1","doi-asserted-by":"crossref","first-page":"851","DOI":"10.1007\/s10618-013-0322-1","article-title":"Classification of time series by shapelet transformation","volume":"28","author":"Hills Jon","year":"2014","unstructured":"Jon Hills , Jason Lines , Edgaras Baranauskas , James Mapp , and Anthony Bagnall . 2014 . Classification of time series by shapelet transformation . Data Mining and Knowledge Discovery 28 , 4 (2014), 851 -- 881 . Jon Hills, Jason Lines, Edgaras Baranauskas, James Mapp, and Anthony Bagnall. 2014. Classification of time series by shapelet transformation. Data Mining and Knowledge Discovery 28, 4 (2014), 851--881.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"e_1_2_1_38_1","doi-asserted-by":"crossref","first-page":"517","DOI":"10.1145\/958942.958948","article-title":"Index-Driven Similarity Search in Metric Spaces","volume":"28","author":"Hjaltason G.R.","year":"2003","unstructured":"G.R. Hjaltason and H. Samet . 2003 . Index-Driven Similarity Search in Metric Spaces . ACM Trans. Database Systems 28 , 4 (2003), 517 -- 580 . G.R. Hjaltason and H. Samet. 2003. Index-Driven Similarity Search in Metric Spaces. ACM Trans. Database Systems 28, 4 (2003), 517--580.","journal-title":"ACM Trans. Database Systems"},{"key":"e_1_2_1_39_1","doi-asserted-by":"crossref","first-page":"530","DOI":"10.1109\/TPAMI.2003.1195989","article-title":"Properties of Embedding Methods for Similarity Searching in Metric Spaces","volume":"25","author":"Hjaltason G.R.","year":"2003","unstructured":"G.R. Hjaltason and H. Samet . 2003 . Properties of Embedding Methods for Similarity Searching in Metric Spaces . IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI) 25 , 5 (2003), 530 -- 549 . G.R. Hjaltason and H. Samet. 2003. Properties of Embedding Methods for Similarity Searching in Metric Spaces. IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI) 25, 5 (2003), 530--549.","journal-title":"IEEE Trans. Pattern Analysis and Machine Intelligence (PAMI)"},{"key":"e_1_2_1_40_1","unstructured":"Bing Hu Yanping Chen and Eamonn Keogh. 2013. Time Series Classification under More Realistic Assumptions. In SDM. 578--586. Bing Hu Yanping Chen and Eamonn Keogh. 2013. Time Series Classification under More Realistic Assumptions. In SDM. 578--586."},{"key":"e_1_2_1_41_1","volume-title":"Proc. Ann. Symp. Foundations of Computer Science (FOCS)","author":"Indyk P.","year":"1999","unstructured":"P. Indyk . 1999 . A Sublinear Time Approximation Scheme for Clustering in Metric Spaces . Proc. Ann. Symp. Foundations of Computer Science (FOCS) (1999), 154--159. P. Indyk. 1999. A Sublinear Time Approximation Scheme for Clustering in Metric Spaces. Proc. Ann. Symp. Foundations of Computer Science (FOCS) (1999), 154--159."},{"key":"e_1_2_1_42_1","doi-asserted-by":"crossref","first-page":"925","DOI":"10.14778\/3380750.3380761","article-title":"Pids: attribute decomposition for improved compression and query performance in columnar storage","volume":"13","author":"Jiang Hao","year":"2020","unstructured":"Hao Jiang , Chunwei Liu , Qi Jin , John Paparrizos , and Aaron J Elmore . 2020 . Pids: attribute decomposition for improved compression and query performance in columnar storage . Proceedings of the VLDB Endowment 13 , 6 (2020), 925 -- 938 . Hao Jiang, Chunwei Liu, Qi Jin, John Paparrizos, and Aaron J Elmore. 2020. Pids: attribute decomposition for improved compression and query performance in columnar storage. Proceedings of the VLDB Endowment 13, 6 (2020), 925--938.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_43_1","volume-title":"Proceedings of the 2021 International Conference on Management of Data. 843--856","author":"Jiang Hao","year":"2021","unstructured":"Hao Jiang , Chunwei Liu , John Paparrizos , Andrew A Chien , Jihong Ma , and Aaron J Elmore . 2021 . Good to the last bit: Data-driven encoding with codecdb . In Proceedings of the 2021 International Conference on Management of Data. 843--856 . Hao Jiang, Chunwei Liu, John Paparrizos, Andrew A Chien, Jihong Ma, and Aaron J Elmore. 2021. Good to the last bit: Data-driven encoding with codecdb. In Proceedings of the 2021 International Conference on Management of Data. 843--856."},{"key":"e_1_2_1_44_1","doi-asserted-by":"crossref","unstructured":"Konstantinos Kalpakis Dhiral Gada and Vasundhara Puttagunta. 2001. Distance measures for effective clustering of ARIMA time-series. In ICDM. 273--280. Konstantinos Kalpakis Dhiral Gada and Vasundhara Puttagunta. 2001. Distance measures for effective clustering of ARIMA time-series. In ICDM. 273--280.","DOI":"10.1109\/ICDM.2001.989529"},{"key":"e_1_2_1_45_1","volume-title":"Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 1334--1342","author":"Kashyap Shrikant","year":"2011","unstructured":"Shrikant Kashyap and Panagiotis Karras . 2011 . Scalable knn search on vertically stored time series . In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 1334--1342 . Shrikant Kashyap and Panagiotis Karras. 2011. Scalable knn search on vertically stored time series. In Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 1334--1342."},{"key":"e_1_2_1_46_1","volume-title":"Proceedings of the 28th International Conference on Very Large Data Bases. VLDB Endowment.","author":"Keogh Eamonn","year":"2002","unstructured":"Eamonn Keogh . 2002 . Exact Indexing of Dynamic Time Warping . In Proceedings of the 28th International Conference on Very Large Data Bases. VLDB Endowment. Eamonn Keogh. 2002. Exact Indexing of Dynamic Time Warping. In Proceedings of the 28th International Conference on Very Large Data Bases. VLDB Endowment."},{"key":"e_1_2_1_47_1","doi-asserted-by":"crossref","first-page":"154","DOI":"10.1007\/s10115-004-0172-7","article-title":"Clustering of time-series subsequences is meaningless: Implications for previous and future research","volume":"8","author":"Keogh Eamonn","year":"2005","unstructured":"Eamonn Keogh and Jessica Lin . 2005 . Clustering of time-series subsequences is meaningless: Implications for previous and future research . Knowledge and Information Systems 8 , 2 (2005), 154 -- 177 . Eamonn Keogh and Jessica Lin. 2005. Clustering of time-series subsequences is meaningless: Implications for previous and future research. Knowledge and Information Systems 8, 2 (2005), 154--177.","journal-title":"Knowledge and Information Systems"},{"key":"e_1_2_1_48_1","doi-asserted-by":"crossref","first-page":"358","DOI":"10.1007\/s10115-004-0154-9","article-title":"Exact indexing of dynamic time warping","volume":"7","author":"Keogh Eamonn","year":"2004","unstructured":"Eamonn Keogh and Chotirat Ann Ratanamahatana . 2004 . Exact indexing of dynamic time warping . Knowledge and Information Systems 7 , 3 (2004), 358 -- 386 . Eamonn Keogh and Chotirat Ann Ratanamahatana. 2004. Exact indexing of dynamic time warping. Knowledge and Information Systems 7, 3 (2004), 358--386.","journal-title":"Knowledge and Information Systems"},{"key":"e_1_2_1_49_1","volume-title":"Data Engineering, 2001. Proceedings. 17th International Conference on. IEEE, 607--614","author":"Kim Sang-Wook","year":"2001","unstructured":"Sang-Wook Kim , Sanghyun Park , and Wesley W Chu . 2001 . An index-based approach for similarity search supporting time warping in large sequence databases . In Data Engineering, 2001. Proceedings. 17th International Conference on. IEEE, 607--614 . Sang-Wook Kim, Sanghyun Park, and Wesley W Chu. 2001. An index-based approach for similarity search supporting time warping in large sequence databases. In Data Engineering, 2001. Proceedings. 17th International Conference on. IEEE, 607--614."},{"key":"e_1_2_1_50_1","doi-asserted-by":"crossref","unstructured":"Chan Kin-pong and Fu Ada. 1999. Efficient Time Series Matching by Wavelets. In ICDE. 126--133. Chan Kin-pong and Fu Ada. 1999. Efficient Time Series Matching by Wavelets. In ICDE. 126--133.","DOI":"10.1109\/ICDE.1999.754915"},{"key":"e_1_2_1_51_1","doi-asserted-by":"crossref","unstructured":"Flip Korn H. V. Jagadish and Christos Faloutsos. 1997. Efficiently Supporting Ad Hoc Queries in Large Datasets of Time Sequences. In SIGMOD. 289--300. Flip Korn H. V. Jagadish and Christos Faloutsos. 1997. Efficiently Supporting Ad Hoc Queries in Large Datasets of Time Sequences. In SIGMOD. 289--300.","DOI":"10.1145\/253262.253332"},{"key":"e_1_2_1_52_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3352020.3352022","article-title":"Artificial intelligence in resource-constrained and shared environments","volume":"53","author":"Krishnan Sanjay","year":"2019","unstructured":"Sanjay Krishnan , Aaron J Elmore , Michael Franklin , John Paparrizos , Zechao Shang , Adam Dziedzic , and Rui Liu . 2019 . Artificial intelligence in resource-constrained and shared environments . ACM SIGOPS Operating Systems Review 53 , 1 (2019), 1 -- 6 . Sanjay Krishnan, Aaron J Elmore, Michael Franklin, John Paparrizos, Zechao Shang, Adam Dziedzic, and Rui Liu. 2019. Artificial intelligence in resource-constrained and shared environments. ACM SIGOPS Operating Systems Review 53, 1 (2019), 1--6.","journal-title":"ACM SIGOPS Operating Systems Review"},{"key":"e_1_2_1_53_1","volume-title":"Proceedings of the Second Workshop on the LLVM Compiler Infrastructure in HPC","author":"Lam S. K.","year":"2015","unstructured":"S. K. Lam , Pitrou A., and S Seibert . 2015 . Numba: A llvm-based python jit compiler . Proceedings of the Second Workshop on the LLVM Compiler Infrastructure in HPC (2015), 1--6. S. K. Lam, Pitrou A., and S Seibert. 2015. Numba: A llvm-based python jit compiler. Proceedings of the Second Workshop on the LLVM Compiler Infrastructure in HPC (2015), 1--6."},{"key":"e_1_2_1_54_1","volume-title":"Faster retrieval with a two-pass dynamic-time-warping lower bound. Pattern recognition 42, 9","author":"Lemire Daniel","year":"2009","unstructured":"Daniel Lemire . 2009. Faster retrieval with a two-pass dynamic-time-warping lower bound. Pattern recognition 42, 9 ( 2009 ), 2169--2180. Daniel Lemire. 2009. Faster retrieval with a two-pass dynamic-time-warping lower bound. Pattern recognition 42, 9 (2009), 2169--2180."},{"key":"e_1_2_1_55_1","volume-title":"Guoren Wang, and Ge Yu.","author":"Lian Xiang","year":"2007","unstructured":"Xiang Lian , Lei Chen , Jeffrey Xu Yu , Guoren Wang, and Ge Yu. 2007 . Similarity match over high speed time-series streams. In ICDE. 1086--1095. Xiang Lian, Lei Chen, Jeffrey Xu Yu, Guoren Wang, and Ge Yu. 2007. Similarity match over high speed time-series streams. In ICDE. 1086--1095."},{"key":"e_1_2_1_56_1","doi-asserted-by":"crossref","unstructured":"Jessica Lin Michail Vlachos Eamonn Keogh and Dimitrios Gunopulos. 2004. Iterative incremental clustering of time series. In EDBT. 106--122. Jessica Lin Michail Vlachos Eamonn Keogh and Dimitrios Gunopulos. 2004. Iterative incremental clustering of time series. In EDBT. 106--122.","DOI":"10.1007\/978-3-540-24741-8_8"},{"key":"e_1_2_1_57_1","doi-asserted-by":"crossref","first-page":"2236","DOI":"10.14778\/3275366.3284968","article-title":"Scalable, variable-length similarity search in data series: The ULISSE approach","volume":"11","author":"Linardi Michele","year":"2018","unstructured":"Michele Linardi and Themis Palpanas . 2018 . Scalable, variable-length similarity search in data series: The ULISSE approach . Proceedings of the VLDB Endowment 11 , 13 (2018), 2236 -- 2248 . Michele Linardi and Themis Palpanas. 2018. Scalable, variable-length similarity search in data series: The ULISSE approach. Proceedings of the VLDB Endowment 11, 13 (2018), 2236--2248.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_58_1","doi-asserted-by":"crossref","first-page":"565","DOI":"10.1007\/s10618-014-0361-2","article-title":"Time series classification with ensembles of elastic distance measures","volume":"29","author":"Lines Jason","year":"2015","unstructured":"Jason Lines and Anthony Bagnall . 2015 . Time series classification with ensembles of elastic distance measures . Data Mining and Knowledge Discovery 29 , 3 (2015), 565 -- 592 . Jason Lines and Anthony Bagnall. 2015. Time series classification with ensembles of elastic distance measures. Data Mining and Knowledge Discovery 29, 3 (2015), 565--592.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"e_1_2_1_59_1","doi-asserted-by":"crossref","first-page":"2586","DOI":"10.14778\/3476249.3476305","article-title":"Decomposed bounded floats for fast compression and queries","volume":"14","author":"Liu Chunwei","year":"2021","unstructured":"Chunwei Liu , Hao Jiang , John Paparrizos , and Aaron J Elmore . 2021 . Decomposed bounded floats for fast compression and queries . Proceedings of the VLDB Endowment 14 , 11 (2021), 2586 -- 2598 . Chunwei Liu, Hao Jiang, John Paparrizos, and Aaron J Elmore. 2021. Decomposed bounded floats for fast compression and queries. Proceedings of the VLDB Endowment 14, 11 (2021), 2586--2598.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_60_1","volume-title":"2008 Eighth IEEE International Conference on Data Mining. IEEE, 413--422","author":"Liu Fei Tony","year":"2008","unstructured":"Fei Tony Liu , Kai Ming Ting , and Zhi-Hua Zhou . 2008 . Isolation forest . In 2008 Eighth IEEE International Conference on Data Mining. IEEE, 413--422 . Fei Tony Liu, Kai Ming Ting, and Zhi-Hua Zhou. 2008. Isolation forest. In 2008 Eighth IEEE International Conference on Data Mining. IEEE, 413--422."},{"key":"e_1_2_1_61_1","first-page":"1","article-title":"AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments","volume":"7","author":"Liu Shinan","year":"2023","unstructured":"Shinan Liu , Tarun Mangla , Ted Shaowang , Jinjin Zhao , John Paparrizos , Sanjay Krishnan , and Nick Feamster . 2023 . AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments . Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7 , 1 (2023), 1 -- 26 . Shinan Liu, Tarun Mangla, Ted Shaowang, Jinjin Zhao, John Paparrizos, Sanjay Krishnan, and Nick Feamster. 2023. AMIR: Active Multimodal Interaction Recognition from Video and Network Traffic in Connected Environments. Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies 7, 1 (2023), 1--26.","journal-title":"Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies"},{"key":"e_1_2_1_62_1","volume-title":"Proceedings of the 9th ACM SIGKDD international conference on knowledge discovery and data mining (SIGKDD). ACM, 216--225","author":"Vlachos","unstructured":"Vlachos M, Hadjieleftheriou M, Gunopulos D, and Keogh E . 2003. Indexing multi-dimensional time-series with support for multiple distance measures . In Proceedings of the 9th ACM SIGKDD international conference on knowledge discovery and data mining (SIGKDD). ACM, 216--225 . Vlachos M, Hadjieleftheriou M, Gunopulos D, and Keogh E. 2003. Indexing multi-dimensional time-series with support for multiple distance measures. In Proceedings of the 9th ACM SIGKDD international conference on knowledge discovery and data mining (SIGKDD). ACM, 216--225."},{"key":"e_1_2_1_63_1","doi-asserted-by":"crossref","first-page":"306","DOI":"10.1109\/TPAMI.2008.76","article-title":"Time Warp Edit Distance with Stiffness Adjustment for Time Series Matching","volume":"31","author":"Marteau Pierre-Fran\u00e7ois","year":"2009","unstructured":"Pierre-Fran\u00e7ois Marteau . 2009 . Time Warp Edit Distance with Stiffness Adjustment for Time Series Matching . IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (2009), 306 -- 318 . Pierre-Fran\u00e7ois Marteau. 2009. Time Warp Edit Distance with Stiffness Adjustment for Time Series Matching. IEEE Transactions on Pattern Analysis and Machine Intelligence 31 (2009), 306--318.","journal-title":"IEEE Transactions on Pattern Analysis and Machine Intelligence"},{"key":"e_1_2_1_64_1","doi-asserted-by":"crossref","first-page":"2684","DOI":"10.1002\/asi.23612","article-title":"Predicting the impact of scientific concepts using full-text features","volume":"67","author":"McKeown Kathy","year":"2016","unstructured":"Kathy McKeown , Hal Daume III , Snigdha Chaturvedi , John Paparrizos , Kapil Thadani , Pablo Barrio , Or Biran , Suvarna Bothe , Michael Collins , Kenneth R Fleischmann , 2016 . Predicting the impact of scientific concepts using full-text features . Journal of the Association for Information Science and Technology 67 , 11 (2016), 2684 -- 2696 . Kathy McKeown, Hal Daume III, Snigdha Chaturvedi, John Paparrizos, Kapil Thadani, Pablo Barrio, Or Biran, Suvarna Bothe, Michael Collins, Kenneth R Fleischmann, et al. 2016. Predicting the impact of scientific concepts using full-text features. Journal of the Association for Information Science and Technology 67, 11 (2016), 2684--2696.","journal-title":"Journal of the Association for Information Science and Technology"},{"key":"e_1_2_1_65_1","volume-title":"Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on. IEEE, 668--679","author":"Megalooikonomou Vasileios","year":"2005","unstructured":"Vasileios Megalooikonomou , Qiang Wang , Guo Li , and Christos Faloutsos . 2005 . A multiresolution symbolic representation of time series . In Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on. IEEE, 668--679 . Vasileios Megalooikonomou, Qiang Wang, Guo Li, and Christos Faloutsos. 2005. A multiresolution symbolic representation of time series. In Data Engineering, 2005. ICDE 2005. Proceedings. 21st International Conference on. IEEE, 668--679."},{"key":"e_1_2_1_66_1","doi-asserted-by":"crossref","unstructured":"Michael D Morse and Jignesh M Patel. 2007. An efficient and accurate method for evaluating time series similarity. In SIGMOD. 569--580. Michael D Morse and Jignesh M Patel. 2007. An efficient and accurate method for evaluating time series similarity. In SIGMOD. 569--580.","DOI":"10.1145\/1247480.1247544"},{"key":"e_1_2_1_67_1","volume-title":"Proceedings of the 2009 SIAM international conference on data mining. SIAM, 473--484","author":"Mueen Abdullah","year":"2009","unstructured":"Abdullah Mueen , Eamonn Keogh , Qiang Zhu , Sydney Cash , and Brandon West-over. 2009 . Exact discovery of time series motifs . In Proceedings of the 2009 SIAM international conference on data mining. SIAM, 473--484 . Abdullah Mueen, Eamonn Keogh, Qiang Zhu, Sydney Cash, and Brandon West-over. 2009. Exact discovery of time series motifs. In Proceedings of the 2009 SIAM international conference on data mining. SIAM, 473--484."},{"key":"e_1_2_1_68_1","first-page":"17","article-title":"Embedding-based subsequence matching in time-series databases","volume":"36","author":"Papapetrou Panagiotis","year":"2011","unstructured":"Panagiotis Papapetrou , Vassilis Athitsos , Michalis Potamias , George Kollios , and Dimitrios Gunopulos . 2011 . Embedding-based subsequence matching in time-series databases . TODS 36 , 3 (2011), 17 . Panagiotis Papapetrou, Vassilis Athitsos, Michalis Potamias, George Kollios, and Dimitrios Gunopulos. 2011. Embedding-based subsequence matching in time-series databases. TODS 36, 3 (2011), 17.","journal-title":"TODS"},{"key":"e_1_2_1_69_1","unstructured":"Ioannis Paparrizos. 2018. Fast Scalable and Accurate Algorithms for Time-Series Analysis. Ph.D. Dissertation. Columbia University. Ioannis Paparrizos. 2018. Fast Scalable and Accurate Algorithms for Time-Series Analysis. Ph.D. Dissertation. Columbia University."},{"key":"e_1_2_1_70_1","unstructured":"J. Paparrizos. 2019. 2018 ucr time-series archive: Backward compatibility missing values and varying lengths. https:\/\/github.com\/johnpaparrizos\/UCRArchiveFixes. J. Paparrizos. 2019. 2018 ucr time-series archive: Backward compatibility missing values and varying lengths. https:\/\/github.com\/johnpaparrizos\/UCRArchiveFixes."},{"key":"e_1_2_1_71_1","doi-asserted-by":"crossref","first-page":"2774","DOI":"10.14778\/3551793.3551830","article-title":"Volume under the surface: a new accuracy evaluation measure for time-series anomaly detection","volume":"15","author":"Paparrizos John","year":"2022","unstructured":"John Paparrizos , Paul Boniol , Themis Palpanas , Ruey S Tsay , Aaron Elmore , and Michael J Franklin . 2022 . Volume under the surface: a new accuracy evaluation measure for time-series anomaly detection . Proceedings of the VLDB Endowment 15 , 11 (2022), 2774 -- 2787 . John Paparrizos, Paul Boniol, Themis Palpanas, Ruey S Tsay, Aaron Elmore, and Michael J Franklin. 2022. Volume under the surface: a new accuracy evaluation measure for time-series anomaly detection. Proceedings of the VLDB Endowment 15, 11 (2022), 2774--2787.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_72_1","volume-title":"2022 IEEE 38th International Conference on Data Engineering (ICDE). IEEE, 2969--2983","author":"Paparrizos John","year":"2022","unstructured":"John Paparrizos , Ikraduya Edian , Chunwei Liu , Aaron J Elmore , and Michael J Franklin . 2022 . Fast adaptive similarity search through variance-aware quantization . In 2022 IEEE 38th International Conference on Data Engineering (ICDE). IEEE, 2969--2983 . John Paparrizos, Ikraduya Edian, Chunwei Liu, Aaron J Elmore, and Michael J Franklin. 2022. Fast adaptive similarity search through variance-aware quantization. In 2022 IEEE 38th International Conference on Data Engineering (ICDE). IEEE, 2969--2983."},{"key":"e_1_2_1_73_1","doi-asserted-by":"crossref","first-page":"1762","DOI":"10.14778\/3342263.3342648","article-title":"GRAIL: efficient time-series representation learning","volume":"12","author":"Paparrizos John","year":"2019","unstructured":"John Paparrizos and Michael J Franklin . 2019 . GRAIL: efficient time-series representation learning . Proceedings of the VLDB Endowment 12 , 11 (2019), 1762 -- 1777 . John Paparrizos and Michael J Franklin. 2019. GRAIL: efficient time-series representation learning. Proceedings of the VLDB Endowment 12, 11 (2019), 1762--1777.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_74_1","volume-title":"Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data. ACM","author":"Paparrizos John","year":"2015","unstructured":"John Paparrizos and Luis Gravano . 2015 . k-shape: Efficient and accurate clustering of time series . In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data. ACM , 1855--1870. John Paparrizos and Luis Gravano. 2015. k-shape: Efficient and accurate clustering of time series. In Proceedings of the 2015 ACM SIGMOD International Conference on Management of Data. ACM, 1855--1870."},{"key":"e_1_2_1_75_1","first-page":"8","article-title":"Fast and Accurate Time-Series Clustering","volume":"42","author":"Paparrizos John","year":"2017","unstructured":"John Paparrizos and Luis Gravano . 2017 . Fast and Accurate Time-Series Clustering . ACM Transactions on Database Systems (TODS) 42 , 2 (2017), 8 . John Paparrizos and Luis Gravano. 2017. Fast and Accurate Time-Series Clustering. ACM Transactions on Database Systems (TODS) 42, 2 (2017), 8.","journal-title":"ACM Transactions on Database Systems (TODS)"},{"key":"e_1_2_1_76_1","doi-asserted-by":"crossref","first-page":"1697","DOI":"10.14778\/3529337.3529354","article-title":"TSB-UAD: an end-to-end benchmark suite for univariate time-series anomaly detection","volume":"15","author":"Paparrizos John","year":"2022","unstructured":"John Paparrizos , Yuhao Kang , Paul Boniol , Ruey S Tsay , Themis Palpanas , and Michael J Franklin . 2022 . TSB-UAD: an end-to-end benchmark suite for univariate time-series anomaly detection . Proceedings of the VLDB Endowment 15 , 8 (2022), 1697 -- 1711 . John Paparrizos, Yuhao Kang, Paul Boniol, Ruey S Tsay, Themis Palpanas, and Michael J Franklin. 2022. TSB-UAD: an end-to-end benchmark suite for univariate time-series anomaly detection. Proceedings of the VLDB Endowment 15, 8 (2022), 1697--1711.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_77_1","unstructured":"John Paparrizos Chunwei Liu Bruno Barbarioli Johnny Hwang Ikraduya Edian Aaron J Elmore Michael J Franklin and Sanjay Krishnan. 2021. VergeDB: A Database for IoT Analytics on Edge Devices.. In CIDR. John Paparrizos Chunwei Liu Bruno Barbarioli Johnny Hwang Ikraduya Edian Aaron J Elmore Michael J Franklin and Sanjay Krishnan. 2021. VergeDB: A Database for IoT Analytics on Edge Devices.. In CIDR."},{"key":"e_1_2_1_78_1","volume-title":"Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. 1887--1905","author":"Paparrizos John","year":"2020","unstructured":"John Paparrizos , Chunwei Liu , Aaron J Elmore , and Michael J Franklin . 2020 . Debunking four long-standing misconceptions of time-series distance measures . In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. 1887--1905 . John Paparrizos, Chunwei Liu, Aaron J Elmore, and Michael J Franklin. 2020. Debunking four long-standing misconceptions of time-series distance measures. In Proceedings of the 2020 ACM SIGMOD International Conference on Management of Data. 1887--1905."},{"key":"e_1_2_1_79_1","volume-title":"Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 559--568","author":"Paparrizos John","year":"2016","unstructured":"John Paparrizos , Ryen W White , and Eric Horvitz . 2016 . Detecting devastating diseases in search logs . In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 559--568 . John Paparrizos, Ryen W White, and Eric Horvitz. 2016. Detecting devastating diseases in search logs. In Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining. 559--568."},{"key":"e_1_2_1_80_1","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1200\/JOP.2015.010504","article-title":"Screening for pancreatic adenocarcinoma using signals from web search logs: Feasibility study and results","volume":"12","author":"Paparrizos John","year":"2016","unstructured":"John Paparrizos , Ryen W White , and Eric Horvitz . 2016 . Screening for pancreatic adenocarcinoma using signals from web search logs: Feasibility study and results . Journal of oncology practice 12 , 8 (2016), 737 -- 744 . John Paparrizos, Ryen W White, and Eric Horvitz. 2016. Screening for pancreatic adenocarcinoma using signals from web search logs: Feasibility study and results. Journal of oncology practice 12, 8 (2016), 737--744.","journal-title":"Journal of oncology practice"},{"key":"e_1_2_1_81_1","doi-asserted-by":"crossref","unstructured":"Chotirat Ann Ratanamahatana and Eamonn Keogh. 2004. Making time-series classification more accurate using learned constraints. In SDM. 11--22. Chotirat Ann Ratanamahatana and Eamonn Keogh. 2004. Making time-series classification more accurate using learned constraints. In SDM. 11--22.","DOI":"10.1137\/1.9781611972740.2"},{"key":"e_1_2_1_82_1","unstructured":"Hiroaki Sakoe and Seibi Chiba. 1971. A dynamic programming approach to continuous speech recognition. In ICA. 65--69. Hiroaki Sakoe and Seibi Chiba. 1971. A dynamic programming approach to continuous speech recognition. In ICA. 65--69."},{"key":"e_1_2_1_83_1","volume-title":"Dynamic programming algorithm optimization for spoken word recognition","author":"Sakoe Hiroaki","year":"1978","unstructured":"Hiroaki Sakoe and Seibi Chiba . 1978. Dynamic programming algorithm optimization for spoken word recognition . IEEE transactions on acoustics, speech, and signal processing 26, 1 ( 1978 ), 43--49. Hiroaki Sakoe and Seibi Chiba. 1978. Dynamic programming algorithm optimization for spoken word recognition. IEEE transactions on acoustics, speech, and signal processing 26, 1 (1978), 43--49."},{"key":"e_1_2_1_84_1","unstructured":"Pavel Senin Jessica Lin Xing Wang Tim Oates Sunil Gandhi Arnold P Boedihardjo Crystal Chen and Susan Frankenstein. 2015. Time series anomaly discovery with grammar-based compression.. In Edbt. 481--492. Pavel Senin Jessica Lin Xing Wang Tim Oates Sunil Gandhi Arnold P Boedihardjo Crystal Chen and Susan Frankenstein. 2015. Time series anomaly discovery with grammar-based compression.. In Edbt. 481--492."},{"key":"e_1_2_1_85_1","volume-title":"Proceedings of the 2018 SIAM International Conference on Data Mining. SIAM, 234--242","author":"Shen Yilin","year":"2018","unstructured":"Yilin Shen , Yanping Chen , Eamonn Keogh , and Hongxia Jin . 2018 . Accelerating time series searching with large uniform scaling . In Proceedings of the 2018 SIAM International Conference on Data Mining. SIAM, 234--242 . Yilin Shen, Yanping Chen, Eamonn Keogh, and Hongxia Jin. 2018. Accelerating time series searching with large uniform scaling. In Proceedings of the 2018 SIAM International Conference on Data Mining. SIAM, 234--242."},{"key":"e_1_2_1_86_1","volume-title":"Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 623--631","author":"Shieh Jin","year":"2008","unstructured":"Jin Shieh and Eamonn Keogh . 2008 . i SAX: indexing and mining terabyte sized time series . In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 623--631 . Jin Shieh and Eamonn Keogh. 2008. i SAX: indexing and mining terabyte sized time series. In Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining. ACM, 623--631."},{"key":"e_1_2_1_87_1","first-page":"2","article-title":"Fast and exact warping of time series using adaptive segmental approximations","volume":"58","author":"Shou Yutao","year":"2005","unstructured":"Yutao Shou , Nikos Mamoulis , and David Cheung . 2005 . Fast and exact warping of time series using adaptive segmental approximations . Machine Learning 58 , 2 -- 3 (2005), 231--267. Yutao Shou, Nikos Mamoulis, and David Cheung. 2005. Fast and exact warping of time series using adaptive segmental approximations. Machine Learning 58, 2--3 (2005), 231--267.","journal-title":"Machine Learning"},{"key":"e_1_2_1_88_1","first-page":"1425","article-title":"The move-split-merge metric for time series","volume":"25","author":"Stefan Alexandra","year":"2013","unstructured":"Alexandra Stefan , Vassilis Athitsos , and Gautam Das . 2013 . The move-split-merge metric for time series . TKDE 25 , 6 (2013), 1425 -- 1438 . Alexandra Stefan, Vassilis Athitsos, and Gautam Das. 2013. The move-split-merge metric for time series. TKDE 25, 6 (2013), 1425--1438.","journal-title":"TKDE"},{"key":"e_1_2_1_89_1","volume-title":"Proceedings of the 2019 SIAM International Conference on Data Mining. SIAM, 522--530","author":"Tan Chang Wei","year":"2019","unstructured":"Chang Wei Tan , Fran\u00e7ois Petitjean , and Geoffrey I Webb . 2019 . Elastic bands across the path: A new framework and method to lower bound DTW . In Proceedings of the 2019 SIAM International Conference on Data Mining. SIAM, 522--530 . Chang Wei Tan, Fran\u00e7ois Petitjean, and Geoffrey I Webb. 2019. Elastic bands across the path: A new framework and method to lower bound DTW. In Proceedings of the 2019 SIAM International Conference on Data Mining. SIAM, 522--530."},{"key":"e_1_2_1_90_1","doi-asserted-by":"crossref","first-page":"231","DOI":"10.1007\/s10618-019-00663-x","article-title":"FastEE: Fast Ensembles of Elastic Distances for time series classification","volume":"34","author":"Tan Chang Wei","year":"2020","unstructured":"Chang Wei Tan , Fran\u00e7ois Petitjean , and Geoffrey I Webb . 2020 . FastEE: Fast Ensembles of Elastic Distances for time series classification . Data Mining and Knowledge Discovery 34 , 1 (2020), 231 -- 272 . Chang Wei Tan, Fran\u00e7ois Petitjean, and Geoffrey I Webb. 2020. FastEE: Fast Ensembles of Elastic Distances for time series classification. Data Mining and Knowledge Discovery 34, 1 (2020), 231--272.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"e_1_2_1_91_1","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s00778-004-0144-2","article-title":"Indexing multidimensional time-series","volume":"15","author":"Vlachos Michail","year":"2006","unstructured":"Michail Vlachos , Marios Hadjieleftheriou , Dimitrios Gunopulos , and Eamonn Keogh . 2006 . Indexing multidimensional time-series . The VLDB Journal 15 , 1 (2006), 1 -- 20 . Michail Vlachos, Marios Hadjieleftheriou, Dimitrios Gunopulos, and Eamonn Keogh. 2006. Indexing multidimensional time-series. The VLDB Journal 15, 1 (2006), 1--20.","journal-title":"The VLDB Journal"},{"key":"e_1_2_1_92_1","volume-title":"Proceedings 18th international conference on data engineering. IEEE, 673--684","author":"Vlachos Michail","year":"2002","unstructured":"Michail Vlachos , George Kollios , and Dimitrios Gunopulos . 2002 . Discovering similar multidimensional trajectories . In Proceedings 18th international conference on data engineering. IEEE, 673--684 . Michail Vlachos, George Kollios, and Dimitrios Gunopulos. 2002. Discovering similar multidimensional trajectories. In Proceedings 18th international conference on data engineering. IEEE, 673--684."},{"key":"e_1_2_1_93_1","doi-asserted-by":"crossref","first-page":"34","DOI":"10.1109\/JPROC.2015.2487976","article-title":"Learning to hash for indexing big data---A survey","volume":"104","author":"Wang Jun","year":"2015","unstructured":"Jun Wang , Wei Liu , Sanjiv Kumar , and Shih-Fu Chang . 2015 . Learning to hash for indexing big data---A survey . Proc. IEEE 104 , 1 (2015), 34 -- 57 . Jun Wang, Wei Liu, Sanjiv Kumar, and Shih-Fu Chang. 2015. Learning to hash for indexing big data---A survey. Proc. IEEE 104, 1 (2015), 34--57.","journal-title":"Proc. IEEE"},{"key":"e_1_2_1_94_1","volume-title":"Heng Tao Shen, et al","author":"Wang Jingdong","year":"2017","unstructured":"Jingdong Wang , Ting Zhang , Nicu Sebe , Heng Tao Shen, et al . 2017 . A survey on learning to hash. IEEE transactions on pattern analysis and machine intelligence 40, 4 (2017), 769--790. Jingdong Wang, Ting Zhang, Nicu Sebe, Heng Tao Shen, et al. 2017. A survey on learning to hash. IEEE transactions on pattern analysis and machine intelligence 40, 4 (2017), 769--790."},{"key":"e_1_2_1_95_1","volume-title":"Experimental comparison of representation methods and distance measures for time series data. Data Mining and Knowledge Discovery","author":"Wang Xiaoyue","year":"2013","unstructured":"Xiaoyue Wang , Abdullah Mueen , Hui Ding , Goce Trajcevski , Peter Scheuermann , and Eamonn Keogh . 2013. Experimental comparison of representation methods and distance measures for time series data. Data Mining and Knowledge Discovery ( 2013 ), 1--35. Xiaoyue Wang, Abdullah Mueen, Hui Ding, Goce Trajcevski, Peter Scheuermann, and Eamonn Keogh. 2013. Experimental comparison of representation methods and distance measures for time series data. Data Mining and Knowledge Discovery (2013), 1--35."},{"key":"e_1_2_1_96_1","doi-asserted-by":"crossref","first-page":"793","DOI":"10.14778\/2536206.2536208","article-title":"A data-adaptive and dynamic segmentation index for whole matching on time series","volume":"6","author":"Wang Yang","year":"2013","unstructured":"Yang Wang , Peng Wang , Jian Pei , Wei Wang , and Sheng Huang . 2013 . A data-adaptive and dynamic segmentation index for whole matching on time series . Proceedings of the VLDB Endowment 6 , 10 (2013), 793 -- 804 . Yang Wang, Peng Wang, Jian Pei, Wei Wang, and Sheng Huang. 2013. A data-adaptive and dynamic segmentation index for whole matching on time series. Proceedings of the VLDB Endowment 6, 10 (2013), 793--804.","journal-title":"Proceedings of the VLDB Endowment"},{"key":"e_1_2_1_97_1","doi-asserted-by":"crossref","first-page":"107895","DOI":"10.1016\/j.patcog.2021.107895","article-title":"Tight lower bounds for dynamic time warping","volume":"115","author":"Webb Geoffrey I","year":"2021","unstructured":"Geoffrey I Webb and Fran\u00e7ois Petitjean . 2021 . Tight lower bounds for dynamic time warping . Pattern Recognition 115 (2021), 107895 . Geoffrey I Webb and Fran\u00e7ois Petitjean. 2021. Tight lower bounds for dynamic time warping. Pattern Recognition 115 (2021), 107895.","journal-title":"Pattern Recognition"},{"key":"e_1_2_1_98_1","doi-asserted-by":"crossref","first-page":"241","DOI":"10.1007\/s10115-008-0131-9","article-title":"Disk aware discord discovery: Finding unusual time series in terabyte sized datasets","volume":"17","author":"Yankov Dragomir","year":"2008","unstructured":"Dragomir Yankov , Eamonn Keogh , and Umaa Rebbapragada . 2008 . Disk aware discord discovery: Finding unusual time series in terabyte sized datasets . Knowledge and Information Systems 17 , 2 (2008), 241 -- 262 . Dragomir Yankov, Eamonn Keogh, and Umaa Rebbapragada. 2008. Disk aware discord discovery: Finding unusual time series in terabyte sized datasets. Knowledge and Information Systems 17, 2 (2008), 241--262.","journal-title":"Knowledge and Information Systems"},{"key":"e_1_2_1_99_1","volume-title":"2016 IEEE 16th international conference on data mining (ICDM). IEEE, 1317--1322","author":"Michael Yeh Chin-Chia","year":"2016","unstructured":"Chin-Chia Michael Yeh , Yan Zhu , Liudmila Ulanova , Nurjahan Begum , Yifei Ding , Hoang Anh Dau , Diego Furtado Silva , Abdullah Mueen , and Eamonn Keogh . 2016 . Matrix profile I: all pairs similarity joins for time series: a unifying view that includes motifs, discords and shapelets . In 2016 IEEE 16th international conference on data mining (ICDM). IEEE, 1317--1322 . Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Diego Furtado Silva, Abdullah Mueen, and Eamonn Keogh. 2016. Matrix profile I: all pairs similarity joins for time series: a unifying view that includes motifs, discords and shapelets. In 2016 IEEE 16th international conference on data mining (ICDM). IEEE, 1317--1322."},{"key":"e_1_2_1_100_1","doi-asserted-by":"crossref","first-page":"83","DOI":"10.1007\/s10618-017-0519-9","article-title":"Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile","volume":"32","author":"Michael Yeh Chin-Chia","year":"2018","unstructured":"Chin-Chia Michael Yeh , Yan Zhu , Liudmila Ulanova , Nurjahan Begum , Yifei Ding , Hoang Anh Dau , Zachary Zimmerman , Diego Furtado Silva , Abdullah Mueen , and Eamonn Keogh . 2018 . Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile . Data Mining and Knowledge Discovery 32 , 1 (2018), 83 -- 123 . Chin-Chia Michael Yeh, Yan Zhu, Liudmila Ulanova, Nurjahan Begum, Yifei Ding, Hoang Anh Dau, Zachary Zimmerman, Diego Furtado Silva, Abdullah Mueen, and Eamonn Keogh. 2018. Time series joins, motifs, discords and shapelets: a unifying view that exploits the matrix profile. Data Mining and Knowledge Discovery 32, 1 (2018), 83--123.","journal-title":"Data Mining and Knowledge Discovery"},{"key":"e_1_2_1_101_1","volume-title":"Data Engineering, 1998. Proceedings.,14th International Conference on. IEEE, 201--208","author":"Yi Byoung-Kee","year":"1998","unstructured":"Byoung-Kee Yi , HV Jagadish , and Christos Faloutsos . 1998 . Efficient retrieval of similar time sequences under time warping . In Data Engineering, 1998. Proceedings.,14th International Conference on. IEEE, 201--208 . Byoung-Kee Yi, HV Jagadish, and Christos Faloutsos. 1998. Efficient retrieval of similar time sequences under time warping. In Data Engineering, 1998. Proceedings.,14th International Conference on. IEEE, 201--208."},{"key":"e_1_2_1_102_1","volume-title":"Proc. ACM-SIAM Symp. Discrete Algorithms","author":"Yianilos P.","year":"1993","unstructured":"P. Yianilos . 1993 . Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces . Proc. ACM-SIAM Symp. Discrete Algorithms (1993), 311--321. P. Yianilos. 1993. Data Structures and Algorithms for Nearest Neighbor Search in General Metric Spaces. Proc. ACM-SIAM Symp. Discrete Algorithms (1993), 311--321."},{"key":"e_1_2_1_103_1","first-page":"843","article-title":"ADS: the adaptive data series index","volume":"25","author":"Zoumpatianos Kostas","year":"2016","unstructured":"Kostas Zoumpatianos , Stratos Idreos , and Themis Palpanas . 2016 . ADS: the adaptive data series index . The VLDB Journal---The International Journal on Very Large Data Bases 25 , 6 (2016), 843 -- 866 . Kostas Zoumpatianos, Stratos Idreos, and Themis Palpanas. 2016. ADS: the adaptive data series index. The VLDB Journal---The International Journal on Very Large Data Bases 25, 6 (2016), 843--866.","journal-title":"The VLDB Journal---The International Journal on Very Large Data Bases"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3594512.3594530","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,10,22]],"date-time":"2024-10-22T20:43:16Z","timestamp":1729629796000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3594512.3594530"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,4]]},"references-count":103,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2023,4]]}},"alternative-id":["10.14778\/3594512.3594530"],"URL":"https:\/\/doi.org\/10.14778\/3594512.3594530","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2023,4]]},"assertion":[{"value":"2023-06-22","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}