{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,13]],"date-time":"2026-04-13T21:10:23Z","timestamp":1776114623950,"version":"3.50.1"},"publisher-location":"New York, NY, USA","reference-count":29,"publisher":"ACM","license":[{"start":{"date-parts":[[2017,5,2]],"date-time":"2017-05-02T00:00:00Z","timestamp":1493683200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"funder":[{"name":"NSERC","award":["PGSD3-438429-2013"],"award-info":[{"award-number":["PGSD3-438429-2013"]}]}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2017,5,2]]},"DOI":"10.1145\/3025453.3025571","type":"proceedings-article","created":{"date-parts":[[2017,5,3]],"date-time":"2017-05-03T12:34:28Z","timestamp":1493814868000},"page":"6683-6694","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":22,"title":["Leveraging Human Routine Models to Detect and Generate Human Behaviors"],"prefix":"10.1145","author":[{"given":"Nikola","family":"Banovic","sequence":"first","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Anqi","family":"Wang","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Yanfeng","family":"Jin","sequence":"additional","affiliation":[{"name":"Middlebury College, Middlebury, VT & Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Christie","family":"Chang","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Julian","family":"Ramos","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Anind","family":"Dey","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]},{"given":"Jennifer","family":"Mankoff","sequence":"additional","affiliation":[{"name":"Carnegie Mellon University, Pittsburgh, PA, USA"}]}],"member":"320","published-online":{"date-parts":[[2017,5,2]]},"reference":[{"key":"e_1_3_2_2_1_1","doi-asserted-by":"publisher","DOI":"10.1145\/1015330.1015430"},{"key":"e_1_3_2_2_2_1","volume-title":"Aggressive driving: Research update","author":"American Automobile Association","unstructured":"American Automobile Association . 2009. Aggressive driving: Research update . American Automobile Association Foundation for Traffic Safety . American Automobile Association. 2009. Aggressive driving: Research update. American Automobile Association Foundation for Traffic Safety."},{"key":"e_1_3_2_2_3_1","doi-asserted-by":"publisher","DOI":"10.1145\/2858036.2858557"},{"key":"e_1_3_2_2_4_1","first-page":"679","article-title":"A Markovian decision process","volume":"6","author":"Bellman Richard","year":"1957","unstructured":"Richard Bellman . 1957 . A Markovian decision process . Journal of Mathematics and Mechanics , 6 , 679 -- 684 . Richard Bellman. 1957. A Markovian decision process. Journal of Mathematics and Mechanics, 6, 679--684.","journal-title":"Journal of Mathematics and Mechanics"},{"key":"e_1_3_2_2_5_1","volume-title":"Pattern Recognition and Machine Learning (Information Science and Statistics)","author":"Bishop Christopher M.","unstructured":"Christopher M. Bishop . 2006. Pattern Recognition and Machine Learning (Information Science and Statistics) . Springer-Verlag New York, Inc. , Secaucus, NJ, USA . Christopher M. Bishop. 2006. Pattern Recognition and Machine Learning (Information Science and Statistics). Springer-Verlag New York, Inc., Secaucus, NJ, USA."},{"key":"e_1_3_2_2_6_1","doi-asserted-by":"publisher","DOI":"10.1145\/1719970.1720011"},{"key":"e_1_3_2_2_7_1","first-page":"175186","article-title":"Interactive pattern search in time series","volume":"2005","author":"Buono Paolo","year":"2005","unstructured":"Paolo Buono , Aleks Aris , Catherine Plaisant , Amir Khella , and Ben Shneiderman . 2005 . Interactive pattern search in time series . In Electronic Imaging 2005 , 175186 . Paolo Buono, Aleks Aris, Catherine Plaisant, Amir Khella, and Ben Shneiderman. 2005. Interactive pattern search in time series. In Electronic Imaging 2005, 175186.","journal-title":"Electronic Imaging"},{"key":"e_1_3_2_2_8_1","doi-asserted-by":"publisher","DOI":"10.1109\/PerCom.2014.6813958"},{"key":"e_1_3_2_2_9_1","volume-title":"Semi-Supervised Learning","author":"Chapelle Olivier","unstructured":"Olivier Chapelle , Bernhard Schlkopf , and Alexander Zien . 2010. Semi-Supervised Learning ( 1 st ed.). The MIT Press . Olivier Chapelle, Bernhard Schlkopf, and Alexander Zien. 2010. Semi-Supervised Learning (1st ed.). The MIT Press.","edition":"1"},{"key":"e_1_3_2_2_10_1","doi-asserted-by":"publisher","DOI":"10.1145\/1978942.1979119"},{"key":"e_1_3_2_2_11_1","doi-asserted-by":"publisher","DOI":"10.1007\/s007790170019"},{"key":"e_1_3_2_2_12_1","doi-asserted-by":"publisher","DOI":"10.1007\/s00265-009-0739-0"},{"key":"e_1_3_2_2_13_1","doi-asserted-by":"publisher","DOI":"10.1109\/ISWC.2012.20"},{"key":"e_1_3_2_2_14_1","doi-asserted-by":"publisher","DOI":"10.2307\/3556620"},{"key":"e_1_3_2_2_15_1","doi-asserted-by":"publisher","DOI":"10.5555\/1564131.1564137"},{"key":"e_1_3_2_2_16_1","first-page":"1","article-title":"Fast generalized subset scan for anomalous pattern detection","volume":"14","author":"McFowland Edward","year":"2013","unstructured":"Edward McFowland , Skyler Speakman , and Daniel B. Neill . 2013 . Fast generalized subset scan for anomalous pattern detection . Journal of Machine Learning Research 14 , 1 (January 2013), 1533--1561. Edward McFowland, Skyler Speakman, and Daniel B. Neill. 2013. Fast generalized subset scan for anomalous pattern detection. Journal of Machine Learning Research 14, 1 (January 2013), 1533--1561.","journal-title":"Journal of Machine Learning Research"},{"key":"e_1_3_2_2_17_1","doi-asserted-by":"publisher","DOI":"10.1093\/oxfordjournals.cje.a013692"},{"key":"e_1_3_2_2_18_1","doi-asserted-by":"publisher","DOI":"10.1145\/2556288.2557321"},{"key":"e_1_3_2_2_19_1","doi-asserted-by":"publisher","DOI":"10.5555\/645530.655656"},{"key":"e_1_3_2_2_20_1","doi-asserted-by":"crossref","unstructured":"Edwin T. Jaynes. 1957. Information theory and statistical mechanics. Physical review 106(4) 620.  Edwin T. Jaynes. 1957. Information theory and statistical mechanics. Physical review 106(4) 620.","DOI":"10.1103\/PhysRev.106.620"},{"key":"e_1_3_2_2_21_1","doi-asserted-by":"publisher","DOI":"10.3758\/BF03200792"},{"key":"e_1_3_2_2_22_1","article-title":"Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data","author":"Mann Gideon S.","year":"2010","unstructured":"Gideon S. Mann and Andrew McCallum . 2010 . Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data . The Journal of Machine Learning Research 11 ( March 2010), 955984. Gideon S. Mann and Andrew McCallum. 2010. Generalized Expectation Criteria for Semi-Supervised Learning with Weakly Labeled Data. The Journal of Machine Learning Research 11 (March 2010), 955984.","journal-title":"The Journal of Machine Learning Research 11"},{"key":"e_1_3_2_2_23_1","volume-title":"Proceedings of the Seventeenth International Conference on Machine Learning (ICML '00)","author":"Andrew","unstructured":"Andrew Y. Ng and Stuart J. Russell. 2000. Algorithms for Inverse Reinforcement Learning . In Proceedings of the Seventeenth International Conference on Machine Learning (ICML '00) , Pat Langley (Ed.). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 663--670. Andrew Y. Ng and Stuart J. Russell. 2000. Algorithms for Inverse Reinforcement Learning. In Proceedings of the Seventeenth International Conference on Machine Learning (ICML '00), Pat Langley (Ed.). Morgan Kaufmann Publishers Inc., San Francisco, CA, USA, 663--670."},{"key":"e_1_3_2_2_24_1","volume-title":"Markov decision processes: discrete stochastic dynamic programming","author":"Puterman Martin L.","unstructured":"Martin L. Puterman . 2014. Markov decision processes: discrete stochastic dynamic programming . John Wiley & Sons, Inc. , New York, NY, USA . Martin L. Puterman. 2014. Markov decision processes: discrete stochastic dynamic programming. John Wiley & Sons, Inc., New York, NY, USA."},{"key":"e_1_3_2_2_25_1","doi-asserted-by":"publisher","DOI":"10.1080\/00140139008925335"},{"key":"e_1_3_2_2_26_1","volume-title":"Learning deep generative models. Annual Review of Statistics and Its Application 2. 361--385","author":"Salakhutdinov Ruslan","year":"2015","unstructured":"Ruslan Salakhutdinov ( 2015 ) Learning deep generative models. Annual Review of Statistics and Its Application 2. 361--385 . Ruslan Salakhutdinov (2015) Learning deep generative models. Annual Review of Statistics and Its Application 2. 361--385."},{"key":"e_1_3_2_2_27_1","doi-asserted-by":"publisher","DOI":"10.1016\/S0001-4575(03)00037-X"},{"key":"e_1_3_2_2_28_1","volume-title":"Proceedings of the 20th International Conference on Machine Learning (ICML-2003)","volume":"2","author":"Zhu Xiaojin","year":"2003","unstructured":"Xiaojin Zhu , Zoubin Ghahramani , and John Lafferty . 2003 . Semi-supervised learning using Gaussian fields and harmonic functions . In Proceedings of the 20th International Conference on Machine Learning (ICML-2003) Volume 2 , vol. 2, 912--919. Xiaojin Zhu, Zoubin Ghahramani, and John Lafferty. 2003. Semi-supervised learning using Gaussian fields and harmonic functions. In Proceedings of the 20th International Conference on Machine Learning (ICML-2003) Volume 2, vol. 2, 912--919."},{"key":"e_1_3_2_2_29_1","volume-title":"Proceedings of the 27th international conference on Machine learning (ICML '10)","author":"Ziebart Brian D.","unstructured":"Brian D. Ziebart , J. Andrew Bagnell , and Anind K. Dey . 2010. Modeling interaction via the principle of maximum causal entropy . In Proceedings of the 27th international conference on Machine learning (ICML '10) . ACM, New York, NY, USA., 1247--1254. Brian D. Ziebart, J. Andrew Bagnell, and Anind K. Dey. 2010. Modeling interaction via the principle of maximum causal entropy. In Proceedings of the 27th international conference on Machine learning (ICML '10). ACM, New York, NY, USA., 1247--1254."}],"event":{"name":"CHI '17: CHI Conference on Human Factors in Computing Systems","location":"Denver Colorado USA","acronym":"CHI '17","sponsor":["SIGCHI ACM Special Interest Group on Computer-Human Interaction"]},"container-title":["Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3025453.3025571","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3025453.3025571","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,6,18]],"date-time":"2025-06-18T03:03:33Z","timestamp":1750215813000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3025453.3025571"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,2]]},"references-count":29,"alternative-id":["10.1145\/3025453.3025571","10.1145\/3025453"],"URL":"https:\/\/doi.org\/10.1145\/3025453.3025571","relation":{},"subject":[],"published":{"date-parts":[[2017,5,2]]},"assertion":[{"value":"2017-05-02","order":2,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}