{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,6,25]],"date-time":"2026-06-25T06:39:39Z","timestamp":1782369579535,"version":"3.54.5"},"reference-count":44,"publisher":"Wiley","license":[{"start":{"date-parts":[[2021,3,25]],"date-time":"2021-03-25T00:00:00Z","timestamp":1616630400000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mobile Information Systems"],"published-print":{"date-parts":[[2021,3,25]]},"abstract":"<jats:p>Facing the massive data of higher education institutions, data mining technology is an intelligent information processing technology that can effectively discover knowledge from the massive data and can discover important information that people have previously ignored from the huge data information. This article is dedicated to the development of applied mathematics education resource mining technology based on edge computing and data stream classification. First of all, this article establishes a resource system architecture suitable for existing applied mathematics education through edge computing technology, which can effectively improve the efficiency of data mining. Secondly, the data stream classification algorithm is used for information extraction and classification integration of massive applied mathematical education data. This method provides potential and valuable information for decision-makers and education practitioners. Finally, the simulation and performance test of the system verify that it has the functions of mathematical information mining and data processing. This system will provide strong support for applied mathematics education reform.<\/jats:p>","DOI":"10.1155\/2021\/5542718","type":"journal-article","created":{"date-parts":[[2021,3,26]],"date-time":"2021-03-26T19:35:08Z","timestamp":1616787308000},"page":"1-8","source":"Crossref","is-referenced-by-count":31,"title":["Research on Mining of Applied Mathematics Educational Resources Based on Edge Computing and Data Stream Classification"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-5996-3838","authenticated-orcid":true,"given":"Liping","family":"Lu","sequence":"first","affiliation":[{"name":"School of Statistics and Mathematics, Henan Finance University, Zhengzhou 451464, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jing","family":"Zhou","sequence":"additional","affiliation":[{"name":"Data Analytics Department, Cabin John Consulting Corp., Arlington, VA 22202, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","reference":[{"key":"1","doi-asserted-by":"publisher","DOI":"10.1109\/tvt.2019.2960103"},{"key":"2","doi-asserted-by":"publisher","DOI":"10.1177\/0825859720935218"},{"key":"3","article-title":"Computation offloading in multi-access edge computing networks: a multi-task learning approach","author":"B. Yang","year":"2020"},{"key":"4","doi-asserted-by":"publisher","DOI":"10.1016\/j.toxlet.2017.07.848"},{"key":"5","doi-asserted-by":"publisher","DOI":"10.1016\/j.dam.2019.11.002"},{"key":"6","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2018.2878154"},{"key":"7","doi-asserted-by":"publisher","DOI":"10.1016\/j.jvs.2018.10.070"},{"key":"8","article-title":"Discriminative structure learning of sum-product networks for data stream classification","volume":"123","author":"Z. Sun","year":"2019","journal-title":"Neural Networks"},{"key":"9","doi-asserted-by":"publisher","DOI":"10.1111\/ans.15243"},{"issue":"7","key":"10","first-page":"1315","article-title":"An incremental construction of deep neuro fuzzy system for continual learning of nonstationary data streams","volume":"28","author":"M. Pratama","year":"2020","journal-title":"IEEE Transactions on Fuzzy Systems"},{"key":"11","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-018-2253-5"},{"key":"12","first-page":"4","article-title":"Acoustic classification in multifrequency echosounder data using deep convolutional neural networks","volume":"4","author":"B. Olav","year":"2020","journal-title":"Ices Journal of Marine Science"},{"key":"13","doi-asserted-by":"publisher","DOI":"10.1111\/ans.15243"},{"key":"14","doi-asserted-by":"publisher","DOI":"10.1016\/j.patcog.2019.01.007"},{"key":"15","doi-asserted-by":"publisher","DOI":"10.1088\/1538-3873\/ab1609"},{"key":"16","doi-asserted-by":"publisher","DOI":"10.1016\/j.otc.2018.01.005"},{"key":"17","article-title":"AwARE: A framework for adaptive recommendation of educational resources","author":"G. M. Machado","year":"2021","journal-title":"Computing"},{"issue":"43","key":"18","first-page":"124","article-title":"Exploiting the stimuli encoding scheme of evolving Spiking Neural Networks for stream learning","volume":"14","author":"J. L. Lobo","year":"2019","journal-title":"Neural Networks"},{"issue":"99","key":"19","article-title":"Joint optimization strategy of computation offloading and resource allocation in multi-access edge computing environment","author":"H. Li","year":"2020","journal-title":"IEEE Transactions on Vehicular Technology"},{"key":"20","doi-asserted-by":"publisher","DOI":"10.1137\/15m1008002"},{"key":"21","doi-asserted-by":"publisher","DOI":"10.4218\/etrij.2020-0112"},{"issue":"11","key":"22","doi-asserted-by":"crossref","first-page":"114501","DOI":"10.1063\/1.5119231","article-title":"Edge computing in space: field programmable gate array-based solutions for spectral and probabilistic analysis of time series","volume":"90","author":"O. Laureniu","year":"2019","journal-title":"Review of Scientific Instruments"},{"issue":"S1","key":"23","doi-asserted-by":"crossref","DOI":"10.1096\/fasebj.2019.33.1_supplement.604.11","article-title":"Millennial students study alone using mixed educational resources","volume":"33","author":"N. Kilarkaje","year":"2019","journal-title":"Faseb Journal"},{"key":"24","doi-asserted-by":"publisher","DOI":"10.1097\/scs.0000000000006207"},{"key":"25","doi-asserted-by":"publisher","DOI":"10.1007\/s11227-019-02864-z"},{"key":"26","first-page":"1","article-title":"Fair and efficient caching algorithms and strategies for peer data sharing in pervasive edge computing environments","author":"Y. Huang","year":"2019","journal-title":"IEEE Transactions on Mobile Computing"},{"key":"27","doi-asserted-by":"publisher","DOI":"10.1016\/j.artmed.2020.101813"},{"key":"28","article-title":"Joint task assignment and resource allocation for d2d-enabled mobile-edge computing","volume":"99","author":"X. Hong","year":"2019","journal-title":"IEEE Transactions on Communications"},{"key":"29","doi-asserted-by":"publisher","DOI":"10.1097\/ss.0000000000000208"},{"key":"30","doi-asserted-by":"publisher","DOI":"10.1097\/ss.0000000000000208"},{"key":"31","doi-asserted-by":"publisher","DOI":"10.1007\/s10994-019-05793-3"},{"key":"32","doi-asserted-by":"publisher","DOI":"10.1287\/moor.2018.0960"},{"key":"33","doi-asserted-by":"publisher","DOI":"10.1007\/s11276-019-02144-x"},{"key":"34","article-title":"Exploiting evolving micro-clusters for data stream classification with emerging class detection","volume":"507","author":"S. U. Din","year":"2019","journal-title":"Information Sciences"},{"key":"35","doi-asserted-by":"publisher","DOI":"10.1111\/ans.15077"},{"key":"36","doi-asserted-by":"publisher","DOI":"10.1021\/acs.jchemed.0c00094"},{"key":"37","doi-asserted-by":"crossref","first-page":"705","DOI":"10.1016\/j.knosys.2018.09.032","article-title":"Selection-based resampling ensemble algorithm for nonstationary imbalanced stream data learning","volume":"163","author":"S. Ren","year":"2018","journal-title":"Knowledge-Based Systems"},{"key":"38","article-title":"Emergency medicine educational resource use in Cape Town: modern or traditional?","author":"A. H. Kleynhans","year":"2017","journal-title":"Postgraduate Medical Journal"},{"key":"39","doi-asserted-by":"publisher","DOI":"10.1145\/3392064"},{"key":"40","doi-asserted-by":"publisher","DOI":"10.1016\/j.jaad.2020.06.041"},{"key":"41","doi-asserted-by":"crossref","first-page":"248","DOI":"10.1016\/j.patcog.2018.10.024","article-title":"Evolving rule-based classifiers with genetic programming on GPUs for drifting data streams","volume":"87","author":"C. Alberto","year":"2019","journal-title":"Pattern Recognition"},{"key":"42","doi-asserted-by":"publisher","DOI":"10.1016\/j.jagp.2017.01.045"},{"issue":"99","key":"43","first-page":"1","article-title":"Resource allocation based on deep reinforcement learning in IoT edge computing","author":"X. Xiong","year":"2020","journal-title":"IEEE Journal on Selected Areas in Communications"},{"key":"44","doi-asserted-by":"publisher","DOI":"10.1002\/hyp.13608"}],"container-title":["Mobile Information Systems"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/downloads.hindawi.com\/journals\/misy\/2021\/5542718.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/misy\/2021\/5542718.xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/downloads.hindawi.com\/journals\/misy\/2021\/5542718.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,12,22]],"date-time":"2022-12-22T15:53:42Z","timestamp":1671724422000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.hindawi.com\/journals\/misy\/2021\/5542718\/"}},"subtitle":[],"editor":[{"given":"Hsu-Yang","family":"Kung","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"editor"}]}],"short-title":[],"issued":{"date-parts":[[2021,3,25]]},"references-count":44,"alternative-id":["5542718","5542718"],"URL":"https:\/\/doi.org\/10.1155\/2021\/5542718","relation":{},"ISSN":["1875-905X","1574-017X"],"issn-type":[{"value":"1875-905X","type":"electronic"},{"value":"1574-017X","type":"print"}],"subject":[],"published":{"date-parts":[[2021,3,25]]}}}