{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,21]],"date-time":"2026-03-21T15:30:21Z","timestamp":1774107021154,"version":"3.50.1"},"reference-count":38,"publisher":"IEEE","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017,12]]},"DOI":"10.1109\/bigdata.2017.8258166","type":"proceedings-article","created":{"date-parts":[[2018,1,15]],"date-time":"2018-01-15T17:47:28Z","timestamp":1516038448000},"page":"2177-2185","source":"Crossref","is-referenced-by-count":22,"title":["Harvey flooding rescue in social media"],"prefix":"10.1109","author":[{"given":"Zhou","family":"Yang","sequence":"first","affiliation":[]},{"given":"Long Hoang","family":"Nguyen","sequence":"additional","affiliation":[]},{"given":"Joshua","family":"Stuve","sequence":"additional","affiliation":[]},{"given":"Guofeng","family":"Cao","sequence":"additional","affiliation":[]},{"given":"Fang","family":"Jin","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref38","first-page":"123","year":"2007","journal-title":"Formal Goodness Of Fit Summary Statistics And Model Selection"},{"key":"ref33","author":"allen","year":"2014","journal-title":"Probability Statistics and Queueing Theory"},{"key":"ref32","author":"leon-garcia","year":"2008","journal-title":"Probability Statistics and Random Processes for Electrical Engineering"},{"key":"ref31","first-page":"135","article-title":"Extension of the law of large numbers to dependent quantities","volume":"15","author":"markov","year":"1906","journal-title":"Izv Fiz-Matem Obsch Kazan Univ (2nd Ser)"},{"key":"ref30","author":"gautam","year":"2007","journal-title":"Operations Research and Management Science Handbook"},{"key":"ref37","article-title":"Stochastic modeling and the theory of queues","author":"wolff","year":"1989","journal-title":"Pearson College Division"},{"key":"ref36","doi-asserted-by":"publisher","DOI":"10.1287\/educ.1110.0083"},{"key":"ref35","first-page":"46","volume":"20","author":"liu","year":"1973","journal-title":"Scheduling algorithms for multiprogramming in a hard-real-time environment"},{"key":"ref34","doi-asserted-by":"publisher","DOI":"10.1109\/TMC.2007.1061"},{"key":"ref10","first-page":"103","article-title":"Text classification from labeled and unlabeled documents using em","author":"nigam","year":"1999","journal-title":"Machine Learning"},{"key":"ref11","doi-asserted-by":"publisher","DOI":"10.1109\/TSMC.1985.6313426"},{"key":"ref12","volume":"21","author":"liao","year":"2002","journal-title":"Using K-nearest Neighbor Classifier for Intrusion Detection"},{"key":"ref13","author":"allahyari","year":"2017","journal-title":"A brief survey of text mining Classification clustering and extraction techniques"},{"key":"ref14","doi-asserted-by":"crossref","first-page":"293","DOI":"10.1023\/A:1018628609742","article-title":"Least squares support vector machine classifiers","volume":"9","author":"suykens","year":"1999","journal-title":"Neural Processing Letters"},{"key":"ref15","author":"manning","year":"2009","journal-title":"Introduction to Information Retrieval 1"},{"key":"ref16","first-page":"629","article-title":"Analysis of first-come-first-serve parallel job scheduling","volume":"98","author":"schwiegelshohn","year":"1998","journal-title":"SODA"},{"key":"ref17","doi-asserted-by":"publisher","DOI":"10.1016\/0166-5316(82)90024-4"},{"key":"ref18","first-page":"591","volume":"31","author":"sivic","year":"2009","journal-title":"Efficient visual search of videos cast as text retrieval"},{"key":"ref19","first-page":"2011","article-title":"An idiots guide to support vector machines (svms)","volume":"21","author":"berwick","year":"2003","journal-title":"Retrieved October"},{"key":"ref28","article-title":"Operations research: algorithms and applications","author":"sen","year":"2010","journal-title":"PHI Learning Pvt Ltd"},{"key":"ref4","doi-asserted-by":"publisher","DOI":"10.1137\/1.9781611974973.68"},{"key":"ref27","author":"taha","year":"1992","journal-title":"Operations Research An Introduction"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-62701-4_2"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1145\/2623330.2623376"},{"key":"ref29","doi-asserted-by":"publisher","DOI":"10.1007\/BF01150051"},{"key":"ref5","author":"jin","year":"2016","journal-title":"Algorithms for modeling mass movements and their adoption in social networks"},{"key":"ref8","doi-asserted-by":"publisher","DOI":"10.1214\/07-SS016"},{"key":"ref7","volume":"2","author":"topi","year":"2014","journal-title":"Computing handbook Information systems and information technology"},{"key":"ref2","first-page":"8","article-title":"Epidemio-logical modeling of news and rumors on twitter","author":"jin","year":"2013","journal-title":"Proc SNAKDD'13"},{"key":"ref1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2014.361"},{"key":"ref9","author":"mccallum","year":"1998","journal-title":"A comparison of event models for naive bayes text classification"},{"key":"ref20","doi-asserted-by":"publisher","DOI":"10.1016\/S0911-6044(03)00059-9"},{"key":"ref22","first-page":"217","article-title":"When Is “Nearest Neighbor","author":"beyer","year":"1999","journal-title":"Berlin Heidelberg Springer Berlin Heidelberg"},{"key":"ref21","doi-asserted-by":"publisher","DOI":"10.2307\/2288950"},{"key":"ref24","doi-asserted-by":"crossref","DOI":"10.1002\/9781118548387","volume":"398","author":"hosmer","year":"2013","journal-title":"Applied Logistic Regression"},{"key":"ref23","first-page":"1","author":"berk","year":"2008","journal-title":"Classification and Regression Trees (CART)"},{"key":"ref26","doi-asserted-by":"publisher","DOI":"10.1002\/047001363X"},{"key":"ref25","doi-asserted-by":"crossref","first-page":"338","DOI":"10.1214\/aoms\/1177728975","article-title":"Stochastic processes occurring in the theory of queues and their analysis by the method of the imbedded markov chain","author":"kendall","year":"1953","journal-title":"The Annals of Mathematical Statistics"}],"event":{"name":"2017 IEEE International Conference on Big Data (Big Data)","location":"Boston, MA","start":{"date-parts":[[2017,12,11]]},"end":{"date-parts":[[2017,12,14]]}},"container-title":["2017 IEEE International Conference on Big Data (Big Data)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/8241556\/8257893\/08258166.pdf?arnumber=8258166","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,10,9]],"date-time":"2019-10-09T07:06:42Z","timestamp":1570604802000},"score":1,"resource":{"primary":{"URL":"http:\/\/ieeexplore.ieee.org\/document\/8258166\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,12]]},"references-count":38,"URL":"https:\/\/doi.org\/10.1109\/bigdata.2017.8258166","relation":{},"subject":[],"published":{"date-parts":[[2017,12]]}}}