{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,12]],"date-time":"2025-12-12T13:32:11Z","timestamp":1765546331370},"reference-count":32,"publisher":"Association for Computing Machinery (ACM)","issue":"8","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Proc. VLDB Endow."],"published-print":{"date-parts":[[2018,4]]},"abstract":"<jats:p>\n            To analyze user behavior over time, it is useful to group users into cohorts, giving rise to\n            <jats:italic>cohort analysis.<\/jats:italic>\n            We identify several crucial limitations of current cohort analysis, motivated by the unmet need for temporal dependence discovery. To address these limitations, we propose a generalization that we call\n            <jats:italic>recurrent cohort analysis.<\/jats:italic>\n            We introduce a set of operators for recurrent cohort analysis and design access methods specific to these operators in both single-node and distributed environments. Through extensive experiments, we show that recurrent cohort analysis when implemented using the proposed access methods is up to six orders faster than one implemented as a layer on top of a database in a single-node setting, and two orders faster than one implemented using Spark SQL in a distributed setting.\n          <\/jats:p>","DOI":"10.14778\/3204028.3204033","type":"journal-article","created":{"date-parts":[[2018,5,22]],"date-time":"2018-05-22T19:56:10Z","timestamp":1527018970000},"page":"893-905","source":"Crossref","is-referenced-by-count":9,"title":["Effective temporal dependence discovery in time series data"],"prefix":"10.14778","volume":"11","author":[{"given":"Qingchao","family":"Cai","sequence":"first","affiliation":[{"name":"National University of Singapore"}]},{"given":"Zhongle","family":"Xie","sequence":"additional","affiliation":[{"name":"National University of Singapore"}]},{"given":"Meihui","family":"Zhang","sequence":"additional","affiliation":[{"name":"Beijing Institute of Technology"}]},{"given":"Gang","family":"Chen","sequence":"additional","affiliation":[{"name":"Zhejiang University"}]},{"given":"H. V.","family":"Jagadish","sequence":"additional","affiliation":[{"name":"University of Michigan"}]},{"given":"Beng Chin","family":"Ooi","sequence":"additional","affiliation":[{"name":"National University of Singapore"}]}],"member":"320","published-online":{"date-parts":[[2018,4]]},"reference":[{"key":"e_1_2_1_1_1","unstructured":"Amplitude. https:\/\/amplitude.com.  Amplitude. https:\/\/amplitude.com."},{"key":"e_1_2_1_2_1","unstructured":"Apache zookeeper. https:\/\/zookeeper.apache.org\/.  Apache zookeeper. https:\/\/zookeeper.apache.org\/."},{"key":"e_1_2_1_3_1","unstructured":"Retention. https:\/\/mixpanel.com\/retention\/.  Retention. https:\/\/mixpanel.com\/retention\/."},{"key":"e_1_2_1_4_1","unstructured":"Rjmetrics. https:\/\/rjmetrics.com\/.  Rjmetrics. https:\/\/rjmetrics.com\/."},{"key":"e_1_2_1_5_1","unstructured":"Top 10 best stock market analysis software review 2018. https:\/\/www.liberatedstocktrader.com\/top-10-best-stock-market-analysis-software-review\/.  Top 10 best stock market analysis software review 2018. https:\/\/www.liberatedstocktrader.com\/top-10-best-stock-market-analysis-software-review\/."},{"key":"e_1_2_1_6_1","unstructured":"Use the cohort analysis report. https:\/\/support.google.com\/analytics\/answer\/6074676?hl=en.  Use the cohort analysis report. https:\/\/support.google.com\/analytics\/answer\/6074676?hl=en."},{"key":"e_1_2_1_7_1","doi-asserted-by":"publisher","DOI":"10.1145\/1142473.1142548"},{"key":"e_1_2_1_8_1","doi-asserted-by":"crossref","unstructured":"K. F. Adams G. C. Fonarow C. L. Emerman T. H. LeJemtel M. R. Costanzo W. T. Abraham R. L. Berkowitz M. Galvao and D. P. Horton. Characteristics and outcomes of patients hospitalized for heart failure in the united states: rationale design and preliminary observations from the first 100 000 cases in the acute decompensated heart failure national registry (adhere). American heart journal 149(2):209--216 2005.  K. F. Adams G. C. Fonarow C. L. Emerman T. H. LeJemtel M. R. Costanzo W. T. Abraham R. L. Berkowitz M. Galvao and D. P. Horton. Characteristics and outcomes of patients hospitalized for heart failure in the united states: rationale design and preliminary observations from the first 100 000 cases in the acute decompensated heart failure national registry (adhere). American heart journal 149(2):209--216 2005.","DOI":"10.1016\/j.ahj.2004.08.005"},{"key":"e_1_2_1_9_1","first-page":"329","volume-title":"VLDB","author":"Amer-Yahia S.","year":"2000","unstructured":"S. Amer-Yahia and T. Johnson . Optimizing queries on compressed bitmaps . In VLDB , pages 329 -- 338 , 2000 . S. Amer-Yahia and T. Johnson. Optimizing queries on compressed bitmaps. In VLDB, pages 329--338, 2000."},{"key":"e_1_2_1_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/2723372.2742797"},{"key":"e_1_2_1_11_1","first-page":"225","volume-title":"CIDR","author":"Boncz P. A.","year":"2005","unstructured":"P. A. Boncz , M. Zukowski , and N. Nes . Monetdb\/x100: Hyper-pipelining query execution . In CIDR , pages 225 -- 237 , 2005 . P. A. Boncz, M. Zukowski, and N. Nes. Monetdb\/x100: Hyper-pipelining query execution. In CIDR, pages 225--237, 2005."},{"key":"e_1_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.1080\/01621459.1983.10477915"},{"key":"e_1_2_1_13_1","volume-title":"Efficient distributed memory management with rdma and caching. Technical report","author":"Cai Q.","year":"2018","unstructured":"Q. Cai , W. Guo , H. Zhang , D. Agrawal , G. Chen , B. C. Ooi , K.-L. Tan , Y. M. Teo , and S. Wang . Efficient distributed memory management with rdma and caching. Technical report , National University of Singapore , Department of Computer Science, 2018 . Q. Cai, W. Guo, H. Zhang, D. Agrawal, G. Chen, B. C. Ooi, K.-L. Tan, Y. M. Teo, and S. Wang. Efficient distributed memory management with rdma and caching. Technical report, National University of Singapore, Department of Computer Science, 2018."},{"key":"e_1_2_1_14_1","doi-asserted-by":"publisher","DOI":"10.1109\/TBDATA.2017.2789286"},{"key":"e_1_2_1_15_1","doi-asserted-by":"publisher","DOI":"10.1145\/1327452.1327492"},{"key":"e_1_2_1_16_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0140-6736(10)60705-2"},{"key":"e_1_2_1_17_1","doi-asserted-by":"crossref","DOI":"10.4135\/9781412983662","volume-title":"Cohort Analysis","author":"Glenn N. D.","year":"2005","unstructured":"N. D. Glenn . Cohort Analysis . Sage Publications, Inc. , London , 2005 . N. D. Glenn. Cohort Analysis. Sage Publications, Inc., London, 2005."},{"key":"e_1_2_1_18_1","doi-asserted-by":"publisher","DOI":"10.1186\/cc4915"},{"key":"e_1_2_1_19_1","doi-asserted-by":"publisher","DOI":"10.14778\/3015270.3015271"},{"key":"e_1_2_1_20_1","doi-asserted-by":"publisher","DOI":"10.1145\/1557019.1557072"},{"key":"e_1_2_1_21_1","volume-title":"Statistical age-period-cohort analysis: a review and critique. Journal of chronic diseases, 38(10):811--830","author":"Kupper L. L.","year":"1985","unstructured":"L. L. Kupper , J. M. Janis , A. Karmous , and B. G. Greenberg . Statistical age-period-cohort analysis: a review and critique. Journal of chronic diseases, 38(10):811--830 , 1985 . L. L. Kupper, J. M. Janis, A. Karmous, and B. G. Greenberg. Statistical age-period-cohort analysis: a review and critique. Journal of chronic diseases, 38(10):811--830, 1985."},{"key":"e_1_2_1_22_1","doi-asserted-by":"publisher","DOI":"10.1145\/2463676.2465322"},{"key":"e_1_2_1_23_1","doi-asserted-by":"publisher","DOI":"10.1007\/s007780000031"},{"key":"e_1_2_1_24_1","doi-asserted-by":"crossref","unstructured":"R. M. Martin P. N. Biswas S. N. Freemantle G. L. Pearce and R. D. Mann. Age and sex distribution of suspected adverse drug reactions to newly marketed drugs in general practice in england: analysis of 48 cohort studies. British journal of clinical pharmacology 46(5):505--511 1998.  R. M. Martin P. N. Biswas S. N. Freemantle G. L. Pearce and R. D. Mann. Age and sex distribution of suspected adverse drug reactions to newly marketed drugs in general practice in england: analysis of 48 cohort studies. British journal of clinical pharmacology 46(5):505--511 1998.","DOI":"10.1046\/j.1365-2125.1998.00817.x"},{"key":"e_1_2_1_25_1","volume-title":"Cohort analysis in social research: Beyond the identification problem","author":"Mason W. M.","year":"2012","unstructured":"W. M. Mason and S. Fienberg . Cohort analysis in social research: Beyond the identification problem . Springer Science & Business Media , 2012 . W. M. Mason and S. Fienberg. Cohort analysis in social research: Beyond the identification problem. Springer Science & Business Media, 2012."},{"issue":"10","key":"e_1_2_1_26_1","first-page":"65","article-title":"An investigation of the accuracy of virtual population analysis using cohort analysis","volume":"9","author":"Pope J. G.","year":"1972","unstructured":"J. G. Pope . An investigation of the accuracy of virtual population analysis using cohort analysis . ICNAF Research Bulletin , 9 ( 10 ): 65 -- 74 , 1972 . J. G. Pope. An investigation of the accuracy of virtual population analysis using cohort analysis. ICNAF Research Bulletin, 9(10):65--74, 1972.","journal-title":"ICNAF Research Bulletin"},{"key":"e_1_2_1_27_1","first-page":"553","volume-title":"VLDB","author":"Stonebraker M.","year":"2005","unstructured":"M. Stonebraker , D. J. Abadi , A. Batkin , X. Chen , M. Cherniack , M. Ferreira , E. Lau , A. Lin , S. Madden , E. O'Neil , P. O'Neil , A. Rasin , N. Tran , and S. Zdonik . C-store: A column-oriented dbms . In VLDB , pages 553 -- 564 , 2005 . M. Stonebraker, D. J. Abadi, A. Batkin, X. Chen, M. Cherniack, M. Ferreira, E. Lau, A. Lin, S. Madden, E. O'Neil, P. O'Neil, A. Rasin, N. Tran, and S. Zdonik. C-store: A column-oriented dbms. In VLDB, pages 553--564, 2005."},{"key":"e_1_2_1_28_1","doi-asserted-by":"publisher","DOI":"10.1145\/362084.362137"},{"key":"e_1_2_1_29_1","doi-asserted-by":"publisher","DOI":"10.1145\/3183713.3193540"},{"key":"e_1_2_1_30_1","first-page":"2","volume-title":"Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing","author":"Zaharia M.","year":"2012","unstructured":"M. Zaharia , M. Chowdhury , T. Das , A. Dave , J. Ma , M. McCauley , M. J. Franklin , S. Shenker , and I. Stoica . Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing . pages 2 -- 2 , 2012 . M. Zaharia, M. Chowdhury, T. Das, A. Dave, J. Ma, M. McCauley, M. J. Franklin, S. Shenker, and I. Stoica. Resilient distributed datasets: A fault-tolerant abstraction for in-memory cluster computing. pages 2--2, 2012."},{"key":"e_1_2_1_31_1","doi-asserted-by":"publisher","DOI":"10.1109\/TKDE.2015.2427795"},{"key":"e_1_2_1_32_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDE.2006.150"}],"container-title":["Proceedings of the VLDB Endowment"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.14778\/3204028.3204033","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,28]],"date-time":"2022-12-28T10:21:15Z","timestamp":1672222875000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.14778\/3204028.3204033"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,4]]},"references-count":32,"journal-issue":{"issue":"8","published-print":{"date-parts":[[2018,4]]}},"alternative-id":["10.14778\/3204028.3204033"],"URL":"https:\/\/doi.org\/10.14778\/3204028.3204033","relation":{},"ISSN":["2150-8097"],"issn-type":[{"value":"2150-8097","type":"print"}],"subject":[],"published":{"date-parts":[[2018,4]]}}}