{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T14:10:11Z","timestamp":1694614211006},"reference-count":86,"publisher":"Wiley","issue":"17","license":[{"start":{"date-parts":[[2011,10,7]],"date-time":"2011-10-07T00:00:00Z","timestamp":1317945600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/onlinelibrary.wiley.com\/termsAndConditions#vor"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Concurrency and Computation"],"published-print":{"date-parts":[[2012,12,10]]},"abstract":"SUMMARY<\/jats:title>Cloud computing has recently attracted great attention, both commercially and academically. MapReduce is a popular programming model for distributed storage and computation in the cloud. In this paper, we survey cloud\u2010based multimedia applications, identifying the open issues and challenges which arise when MapReduce is used for cloud computing. Copyright \u00a9 2011 John Wiley & Sons, Ltd.<\/jats:p>","DOI":"10.1002\/cpe.1846","type":"journal-article","created":{"date-parts":[[2011,10,7]],"date-time":"2011-10-07T21:13:02Z","timestamp":1318021982000},"page":"2083-2101","source":"Crossref","is-referenced-by-count":5,"title":["Multimedia Applications and Security in MapReduce: Opportunities and Challenges"],"prefix":"10.1002","volume":"24","author":[{"given":"Zhiwei","family":"Yu","sequence":"first","affiliation":[{"name":"School of Software Tsinghua University, Key Laboratory for Information System Security, Ministry of Education Tsinghua National Laboratory for Information Science and Technology Beijing China"}]},{"given":"Chaokun","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Software Tsinghua University, Key Laboratory for Information System Security, Ministry of Education Tsinghua National Laboratory for Information Science and Technology Beijing China"}]},{"given":"Clark","family":"Thomborson","sequence":"additional","affiliation":[{"name":"Department of Computer Science The University of Auckland New Zealand"}]},{"given":"Jianmin","family":"Wang","sequence":"additional","affiliation":[{"name":"School of Software Tsinghua University, Key Laboratory for Information System Security, Ministry of Education Tsinghua National Laboratory for Information Science and Technology Beijing China"}]},{"given":"Shiguo","family":"Lian","sequence":"additional","affiliation":[{"name":"Huawei Research Institute Huawei Technologies Co., Ltd. Beijing China"}]},{"given":"Athanasios V.","family":"Vasilakos","sequence":"additional","affiliation":[{"name":"University of Western Macedonia Kozani Greece"}]}],"member":"311","published-online":{"date-parts":[[2011,10,7]]},"reference":[{"key":"e_1_2_9_2_1","unstructured":"ArmbrustMet al.Above the clouds: A Berkeley view of cloud computing.Technical Report UCB\/EECS\u20102009\u201028 EECS Department University of California Berkeley Febuary2009."},{"key":"e_1_2_9_3_1","unstructured":"MellP GranceT.The NIST definition of cloud computing (draft): Recommendations of the National Institute of Standards and Technology.Technical Report 800\u2010145 NIST US Department of Commerce Jan2011."},{"key":"e_1_2_9_4_1","unstructured":"Cloud Security Alliance.Security guidance for critical areas of focus v2.1 2009."},{"key":"e_1_2_9_5_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.jnca.2010.07.006"},{"key":"e_1_2_9_6_1","doi-asserted-by":"publisher","DOI":"10.1109\/MC.2009.20"},{"key":"e_1_2_9_7_1","unstructured":"NatisYVet al.Application infrastructure for cloud computing: A growing market.Technical Report G00175138 Gartner Research Mar2010."},{"key":"e_1_2_9_8_1","unstructured":"SmithDM.Hype cycle for cloud computing.Technical Report G00201557 Gartner Research Jul2010."},{"key":"e_1_2_9_9_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-1-84996-241-4_2"},{"key":"e_1_2_9_10_1","doi-asserted-by":"crossref","unstructured":"DahburK MohammadB TarakjiAB.A survey of risks threats and vulnerabilities in cloud computing.Proceedings of the 2011 International Conference on Intelligent Semantic Web\u2010Services and Applications ISWSA '11 ACM: New York NY USA 2011;12:1\u201312:6 DOI:10.1145\/1980822.1980834.","DOI":"10.1145\/1980822.1980834"},{"key":"e_1_2_9_11_1","doi-asserted-by":"publisher","DOI":"10.2498\/cit.1001864"},{"key":"e_1_2_9_12_1","unstructured":"Hadoop.http:\/\/hadoop.apache.org\/[Accessed on August 12 2011]."},{"key":"e_1_2_9_13_1","doi-asserted-by":"crossref","unstructured":"FosterI ZhaoY RaicuI LuS.Cloud computing and grid computing 360\u2010degree compared.Grid Computing Environments Workshop (GCE '08) Nov2008;1\u201310 DOI:10.1109\/GCE.2008.4738445.","DOI":"10.1109\/GCE.2008.4738445"},{"key":"e_1_2_9_14_1","unstructured":"DeanJ GhemawatS.MapReduce: Simplified data processing on large clusters.OSDI 2004;137\u2013150."},{"key":"e_1_2_9_15_1","unstructured":"apache.org\/hadoop\/poweredby.http:\/\/wiki.apache.org\/hadoop\/PoweredBy."},{"key":"e_1_2_9_16_1","doi-asserted-by":"crossref","unstructured":"PavloA PaulsonE RasinA AbadiDJ DeWittDJ MaddenS StonebrakerM.A comparison of approaches to large\u2010scale data analysis.SIGMOD Conference 2009;165\u2013178.","DOI":"10.1145\/1559845.1559865"},{"issue":"1","key":"e_1_2_9_17_1","first-page":"922","article-title":"HadoopDB: An architectural hybrid of MapReduce and DBMS technologies for analytical workloads","volume":"2","author":"Abouzeid A","year":"2009","journal-title":"PVLDB"},{"issue":"1","key":"e_1_2_9_18_1","first-page":"518","article-title":"Hadoop++: Making a yellow elephant run like a cheetah (without it even noticing)","volume":"3","author":"Dittrich J","year":"2010","journal-title":"PVLDB"},{"issue":"6","key":"e_1_2_9_19_1","first-page":"385","article-title":"Automatic optimization for MapReduce programs","volume":"4","author":"Jahani E","year":"2011","journal-title":"PVLDB"},{"key":"e_1_2_9_20_1","doi-asserted-by":"publisher","DOI":"10.14778\/1687553.1687609"},{"issue":"2","key":"e_1_2_9_21_1","first-page":"1414","article-title":"Building a highlevel dataflow system on top of MapReduce: The pig experience","volume":"2","author":"Gates A","year":"2009","journal-title":"PVLDB"},{"key":"e_1_2_9_22_1","doi-asserted-by":"crossref","unstructured":"OlstonC ReedB SrivastavaU KumarR TomkinsA.Pig latin: A not\u2010so\u2010foreign language for data processing.SIGMOD Conference 2008;1099\u20131110.","DOI":"10.1145\/1376616.1376726"},{"key":"e_1_2_9_23_1","unstructured":"ZahariaM KonwinskiA JosephAD KatzRH StoicaI.Improving MapReduce performance in heterogeneous environments.OSDI 2008;29\u201342."},{"key":"e_1_2_9_24_1","unstructured":"CondieT ConwayN AlvaroP HellersteinJM ElmeleegyK SearsR.MapReduce online.NSDI 2010;313\u2013328."},{"issue":"1","key":"e_1_2_9_25_1","first-page":"285","article-title":"Haloop: Efficient iterative data processing on large clusters","volume":"3","author":"Bu Y","year":"2010","journal-title":"PVLDB"},{"key":"e_1_2_9_26_1","doi-asserted-by":"publisher","DOI":"10.1016\/j.scico.2007.07.001"},{"key":"e_1_2_9_27_1","doi-asserted-by":"publisher","DOI":"10.1006\/jpdc.1996.0033"},{"key":"e_1_2_9_28_1","doi-asserted-by":"publisher","DOI":"10.1006\/jpdc.1994.1038"},{"key":"e_1_2_9_29_1","volume-title":"Daytona\u2013Developer Guide","author":"eXtreme Computing Group M","year":"2011"},{"key":"e_1_2_9_30_1","doi-asserted-by":"crossref","unstructured":"LinJ DyerC.Data intensive text processing with MapReduce 2010.","DOI":"10.1007\/978-3-031-02136-7"},{"key":"e_1_2_9_31_1","doi-asserted-by":"crossref","unstructured":"ElsayedT LinJJ OardDW.Pairwise document similarity in large collections with MapReduce.ACL (Short Papers) 2008;265\u2013268.","DOI":"10.3115\/1557690.1557767"},{"key":"e_1_2_9_32_1","doi-asserted-by":"crossref","unstructured":"WangC WangJ LinX WangW WangH LiH TianW XuJ LiR.MapDupReducer: Detecting near duplicates over massive datasets.Proceedings of the 2010 International Conference on Management of Data SIGMOD '10 ACM: New York NY USA 2010;1119\u20131122 DOI:10.1145\/1807167.1807296.","DOI":"10.1145\/1807167.1807296"},{"key":"e_1_2_9_33_1","doi-asserted-by":"crossref","unstructured":"LiR JuL PengZ YuZ WangC.Batch text similarity search with MapReduce.To appear 13th International Asia\u2010Pacific Web Conference (APWeb) 2011.","DOI":"10.1007\/978-3-642-20291-9_46"},{"key":"e_1_2_9_34_1","first-page":"95","article-title":"A new agglomerative hierarchical clustering algorithm implementation based on the map reduce framework","author":"Gao H","year":"2010","journal-title":"International Journal of Digital Content Technology and its Applications"},{"key":"e_1_2_9_35_1","doi-asserted-by":"publisher","DOI":"10.1186\/1471\u20102105\u201010\u201046"},{"key":"e_1_2_9_36_1","doi-asserted-by":"crossref","unstructured":"YanR FleuryM\u2010O MerlerM NatsevA SmithJR.Large\u2010scale multimedia semantic concept modeling using robust subspace bagging and MapReduce.Proceedings of the First ACM Workshop on Large\u2010scale Multimedia Retrieval and Mining LS\u2010MMRM '09 ACM: New York NY USA 2009;35\u201342 DOI:10.1145\/1631058.1631067.","DOI":"10.1145\/1631058.1631067"},{"key":"e_1_2_9_37_1","doi-asserted-by":"publisher","DOI":"10.1007\/978\u20103\u2010642\u201011756\u20105"},{"issue":"6","key":"e_1_2_9_38_1","article-title":"Mobile multimedia services over cloud computing","volume":"5","author":"Lai CF","year":"2010","journal-title":"E\u2010Letter"},{"key":"e_1_2_9_39_1","doi-asserted-by":"crossref","unstructured":"YangZ KamataS AhraryA.Nir: Content based image retrieval on cloud computing.Intelligent Computing and Intelligent Systems 2009. ICIS 2009. IEEE International Conference on Vol. 3 2009;556\u2013559 DOI:10.1109\/ICICISYS.2009.5358101.","DOI":"10.1109\/ICICISYS.2009.5358101"},{"key":"e_1_2_9_40_1","doi-asserted-by":"crossref","unstructured":"ChangFC HuangHC.A programming model for distributed content\u2010based image retrieval.Intelligent Information Hiding and Multimedia Signal Processing 2007. IIHMSP 2007. Third International Conference on Vol. 1 2007;210\u2013213 DOI:10.1109\/IIH\u2010MSP.2007.54.","DOI":"10.1109\/IIH-MSP.2007.54"},{"issue":"98","key":"e_1_2_9_41_1","first-page":"1","article-title":"Sequential minimal optimization: A fast algorithm for training support vector machines","volume":"208","author":"Platt J","year":"1998","journal-title":"Advances in Kernel Methods: Support Vector Learning"},{"key":"e_1_2_9_42_1","doi-asserted-by":"crossref","unstructured":"CatanzaroB SundaramN KeutzerK.Fast support vector machine training and classification on graphics processors.Proceedings of the 25th International Conference on Machine Learning (ICML 2008) Helsinki Finland 2008;104\u2013111.","DOI":"10.1145\/1390156.1390170"},{"key":"e_1_2_9_43_1","doi-asserted-by":"crossref","unstructured":"AlhamN LiM HammoudS LiuY PonrajM.A distributed SVM for image annotation.Fuzzy Systems and Knowledge Discovery (FSKD) 2010 Seventh International Conference on Vol. 6 2010;2983\u20132987 DOI:10.1109\/FSKD.2010.5569084.","DOI":"10.1109\/FSKD.2010.5569084"},{"key":"e_1_2_9_44_1","doi-asserted-by":"crossref","unstructured":"LiuT RosenbergC RowleyHA.Clustering billions of images with large scale nearest neighbor search.Proceedings of the Eighth IEEE Workshop on Applications of Computer Vision WACV '07 IEEE Computer Society: Washington DC USA 2007;28\u2013 DOI:10.1109\/WACV.2007.18.","DOI":"10.1109\/WACV.2007.18"},{"key":"e_1_2_9_45_1","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-642-16515-3_21"},{"key":"e_1_2_9_46_1","doi-asserted-by":"crossref","unstructured":"LiB ZhaoH LvZ.Parallel isodata clustering of remote sensing images based on MapReduce.Cyber\u2010Enabled Distributed Computing and Knowledge Discovery (CyberC) 2010 International Conference on 2010;380\u2013383 DOI:10.1109\/CyberC.2010.75.","DOI":"10.1109\/CyberC.2010.75"},{"key":"e_1_2_9_47_1","unstructured":"LiuKet al.A distributed parallel image analysis platform with MapReduce integration.Technical Report HPL\u20102010\u201071 HP Labs July2010."},{"key":"e_1_2_9_48_1","doi-asserted-by":"crossref","unstructured":"CaryA SunZ HristidisV RisheN.Experiences on processing spatial data with MapReduce.Proceedings of the 21st International Conference on Scientific and Statistical Database Management SSDBM 2009 Springer\u2010Verlag:Berlin Heidelberg 2009;302\u2013319.","DOI":"10.1007\/978-3-642-02279-1_24"},{"key":"e_1_2_9_49_1","doi-asserted-by":"crossref","unstructured":"WhiteB YehT LinJ DavisL.Web\u2010scale computer vision using MapReduce for multimedia data mining.Proceedings of the Tenth International Workshop on Multimedia Data Mining MDMKDD '10 ACM: New York NY USA 2010;9:1\u20139:10 DOI:10.1145\/1814245.1814254.","DOI":"10.1145\/1814245.1814254"},{"key":"e_1_2_9_50_1","doi-asserted-by":"crossref","unstructured":"HeB FangW LuoQ GovindarajuNK WangT.Mars: A MapReduce framework on graphics processors.PACT 2008;260\u2013269.","DOI":"10.1145\/1454115.1454152"},{"key":"e_1_2_9_51_1","unstructured":"Shimin ChenSWS.Map\u2010reduce meets wider varieties of applications.Technical Report May2008."},{"key":"e_1_2_9_52_1","unstructured":"BennettJ LanningS NetflixN.The netflix prize.In KDD Cup and Workshop in conjunction with KDD 2007."},{"key":"e_1_2_9_53_1","doi-asserted-by":"crossref","unstructured":"AkcelikV BielakJ BirosG EpanomeritakisI FernandezA GhattasO KimEJ LopezJ O'HallaronD TuT et al.High resolution forward and inverse earthquake modeling on terascale computers.Proceedings of the 2003 ACM\/IEEE Conference on Supercomputing SC '03 IEEE Computer Society:Washington DC USA 2003;52\u2013.","DOI":"10.1145\/1048935.1050202"},{"key":"e_1_2_9_54_1","first-page":"66","volume-title":"11th Annual Conference of the International Speech Communication Association (INTERSPEECH 2010)","author":"Beaufays F","year":"2010"},{"key":"e_1_2_9_55_1","doi-asserted-by":"crossref","unstructured":"JehanT LamereP WhitmanB.Music retrieval from everything.Proceedings of the international conference on Multimedia information retrieval MIR '10 ACM: New York NY USA 2010;245\u2013246 DOI:10.1145\/1743384.1743428. URLhttp:\/\/doi.acm.org\/10.1145\/1743384.1743428.","DOI":"10.1145\/1743384.1743428"},{"key":"e_1_2_9_56_1","unstructured":"YoshiiK GotoM.Continuous PLSI and smoothing techniques for hybrid music recommendation.ISMIR 2009 2009;339\u2013344."},{"key":"e_1_2_9_57_1","doi-asserted-by":"crossref","unstructured":"ZhaoZ WangX XiangQ SarroffAM LiZ WangY.Large\u2010scale music tag recommendation with explicit multiple attributes.ACM Multimedia 2010;401\u2013410.","DOI":"10.1145\/1873951.1874006"},{"key":"e_1_2_9_58_1","doi-asserted-by":"crossref","unstructured":"LiuKY ZhangT WangL.A new parallel video understanding and retrieval system.ICME 2010;679\u2013684.","DOI":"10.1109\/ICME.2010.5583873"},{"key":"e_1_2_9_59_1","doi-asserted-by":"crossref","unstructured":"SebastineSC ThuraisinghamBM PrabhakaranB.Semantic web for content based video retrieval.ICSC 2009;103\u2013108.","DOI":"10.1109\/ICSC.2009.49"},{"key":"e_1_2_9_60_1","doi-asserted-by":"crossref","unstructured":"BalujaS SethR SivakumarD JingY YagnikJ KumarS RavichandranD AlyM.Video suggestion and discovery for youtube: Taking random walks through the view graph.WWW 2008;895\u2013904.","DOI":"10.1145\/1367497.1367618"},{"key":"e_1_2_9_61_1","doi-asserted-by":"crossref","unstructured":"JinY HuM SinghH XieZ.Myspace video recommendation with map\u2010reduce on qizmt2010.","DOI":"10.1109\/ICSC.2010.79"},{"key":"e_1_2_9_62_1","doi-asserted-by":"publisher","DOI":"10.1109\/CLOUD.2010.73"},{"key":"e_1_2_9_63_1","doi-asserted-by":"publisher","DOI":"10.1109\/MCSE.2009.120"},{"key":"e_1_2_9_64_1","doi-asserted-by":"crossref","unstructured":"MalewiczG AusternMH BikAJ DehnertJC HornI LeiserN CzajkowskiG.Pregel: A system for large\u2010scale graph processing.Proceedings of the 2010 International Conference on Management of Data SIGMOD '10 ACM: New York NY USA 2010;135\u2013146 DOI:10.1145\/1807167.1807184.","DOI":"10.1145\/1807167.1807184"},{"key":"e_1_2_9_65_1","doi-asserted-by":"crossref","unstructured":"RaoD YarowskyD.Ranking and semi\u2010supervised classification on large scale graphs using map\u2010reduce.Proceedings of the 2009 Workshop on Graph\u2010based Methods for Natural Language Processing TextGraphs\u20104 Association for Computational Linguistics: Stroudsburg PA USA 2009;58\u201365.","DOI":"10.3115\/1708124.1708137"},{"key":"e_1_2_9_66_1","doi-asserted-by":"crossref","unstructured":"ChoiH SonJ ChoY SungMK ChungYD.SPIDER: A system for scalable parallel \/ distributed evaluation of large\u2010scale RDF data.CIKM 2009;2087\u20132088.","DOI":"10.1145\/1645953.1646315"},{"key":"e_1_2_9_67_1","doi-asserted-by":"crossref","unstructured":"HusainMF DoshiP KhanL ThuraisinghamBM.Storage and retrieval of large RDF graph using Hadoop and MapReduce.CloudCom 2009;680\u2013686.","DOI":"10.1007\/978-3-642-10665-1_72"},{"key":"e_1_2_9_68_1","doi-asserted-by":"crossref","unstructured":"KangU TsourakakisCE FaloutsosC.Pegasus: A peta\u2010scale graph mining system implementation and observations.Proceedings of the 2009 Ninth IEEE International Conference on Data Mining. ICDM '09 IEEE Computer Society: Washington DC USA 2009;229\u2013238 DOI:10.1109\/ICDM.2009.14.","DOI":"10.1109\/ICDM.2009.14"},{"key":"e_1_2_9_69_1","doi-asserted-by":"crossref","unstructured":"LinJ SchatzM.Design patterns for efficient graph algorithms in MapReduce.Proceedings of the Eighth Workshop on Mining and Learning with Graphs MLG '10 ACM: New York NY USA 2010;78\u201385 DOI:10.1145\/1830252.1830263.","DOI":"10.1145\/1830252.1830263"},{"key":"e_1_2_9_70_1","doi-asserted-by":"crossref","unstructured":"PapadimitriouS SunJ.DisCo: Distributed co\u2010clustering with map\u2010reduce: A case study towards petabyte\u2010scale end\u2010to\u2010end mining.ICDM 2008;512\u2013521.","DOI":"10.1109\/ICDM.2008.142"},{"issue":"1","key":"e_1_2_9_71_1","first-page":"3","article-title":"Recent advances in multimedia information system security","volume":"33","author":"Lian S","year":"2009","journal-title":"Informatica (Slovenia)"},{"key":"e_1_2_9_72_1","doi-asserted-by":"publisher","DOI":"10.1007\/s12394\u2010008\u20100005\u2010z"},{"key":"e_1_2_9_73_1","unstructured":"Gartner Global IT Council for Cloud Services.Rights and responsibilities for consumers of cloud computing services.Technical Report Gartner Research 2010."},{"key":"e_1_2_9_74_1","doi-asserted-by":"publisher","DOI":"10.1007\/978\u20103\u2010642\u201011756\u20105"},{"key":"e_1_2_9_75_1","doi-asserted-by":"publisher","DOI":"10.4018\/978-1-60566-262-6"},{"key":"e_1_2_9_76_1","doi-asserted-by":"crossref","unstructured":"WeiW DuJ YuT GuX.SecureMR: A service integrity assurance framework for MapReduce.ACSAC 2009;73\u201382.","DOI":"10.1109\/ACSAC.2009.17"},{"key":"e_1_2_9_77_1","unstructured":"RoyI SettySTV KilzerA ShmatikovV WitchelE.Airavat: Security and privacy for MapReduce.NSDI 2010;297\u2013312."},{"key":"e_1_2_9_78_1","doi-asserted-by":"crossref","unstructured":"DworkC.Differential privacy.ICALP (2) 2006;1\u201312.","DOI":"10.1007\/11787006_1"},{"key":"e_1_2_9_79_1","volume-title":"SELinux: NSA's Open Source Security Enhanced Linux","author":"McCarty B","year":"2004"},{"key":"e_1_2_9_80_1","doi-asserted-by":"crossref","unstructured":"ZhuH BaoF.Private searching on MapReduce.TrustBus 2010;93\u2013101.","DOI":"10.1007\/978-3-642-15152-1_9"},{"key":"e_1_2_9_81_1","doi-asserted-by":"crossref","unstructured":"ZhouW SherrM MarczakWR ZhangZ TaoT LooBT LeeI.Towards a data\u2010centric view of cloud security.Proceedings of the Second International Workshop on Cloud Data Management CloudDB '10 ACM: New York NY USA 2010;25\u201332 DOI:10.1145\/1871929.1871934.","DOI":"10.1145\/1871929.1871934"},{"key":"e_1_2_9_82_1","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2010.70"},{"key":"e_1_2_9_83_1","doi-asserted-by":"publisher","DOI":"10.1145\/1653662.1653687"},{"key":"e_1_2_9_84_1","doi-asserted-by":"crossref","unstructured":"FuJ WangC YuZ WangJ SunJG.A watermark\u2010aware trusted running environment for software clouds.ChinaGrid Conference (ChinaGrid) 2010 Fifth Annual 2010;144\u2013151 DOI:10.1109\/ChinaGrid.2010.15.","DOI":"10.1109\/ChinaGrid.2010.15"},{"key":"e_1_2_9_85_1","doi-asserted-by":"publisher","DOI":"10.1155\/2011\/837209"},{"key":"e_1_2_9_86_1","doi-asserted-by":"crossref","unstructured":"ZouP WangC LiuZ BaoD.Phosphor: A cloud based DRM scheme with SIM card.APWeb 2010;459\u2013463.","DOI":"10.1109\/APWeb.2010.43"},{"key":"e_1_2_9_87_1","doi-asserted-by":"publisher","DOI":"10.1002\/spe.1088"}],"container-title":["Concurrency and Computation: Practice and Experience"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.wiley.com\/onlinelibrary\/tdm\/v1\/articles\/10.1002%2Fcpe.1846","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/pdf\/10.1002\/cpe.1846","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,9,13]],"date-time":"2023-09-13T01:19:14Z","timestamp":1694567954000},"score":1,"resource":{"primary":{"URL":"https:\/\/onlinelibrary.wiley.com\/doi\/10.1002\/cpe.1846"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2011,10,7]]},"references-count":86,"journal-issue":{"issue":"17","published-print":{"date-parts":[[2012,12,10]]}},"alternative-id":["10.1002\/cpe.1846"],"URL":"https:\/\/doi.org\/10.1002\/cpe.1846","archive":["Portico"],"relation":{},"ISSN":["1532-0626","1532-0634"],"issn-type":[{"value":"1532-0626","type":"print"},{"value":"1532-0634","type":"electronic"}],"subject":[],"published":{"date-parts":[[2011,10,7]]}}}