{"id":"https://openalex.org/W2897821674","doi":"https://doi.org/10.1109/access.2018.2875742","title":"Predicting Achievement of Students in Smart Campus","display_name":"Predicting Achievement of Students in Smart Campus","publication_year":2018,"publication_date":"2018-01-01","ids":{"openalex":"https://openalex.org/W2897821674","doi":"https://doi.org/10.1109/access.2018.2875742","mag":"2897821674"},"language":"en","primary_location":{"id":"doi:10.1109/access.2018.2875742","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2875742","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.1109/access.2018.2875742","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036145324","display_name":"Shaojie Qu","orcid":"https://orcid.org/0000-0003-4237-1961"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Shaojie Qu","raw_affiliation_strings":["Network Information Technology Center, Beijing Institute of Technology, Beijing, China"],"raw_orcid":"https://orcid.org/0000-0003-4237-1961","affiliations":[{"raw_affiliation_string":"Network Information Technology Center, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100342160","display_name":"Kan Li","orcid":"https://orcid.org/0000-0003-3528-4739"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kan Li","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101843962","display_name":"Shuhui Zhang","orcid":"https://orcid.org/0000-0001-5017-3207"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuhui Zhang","raw_affiliation_strings":["Network Information Technology Center, Beijing Institute of Technology, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Network Information Technology Center, Beijing Institute of Technology, Beijing, China","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5100635290","display_name":"Yongchao Wang","orcid":"https://orcid.org/0000-0001-6394-4701"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yongchao Wang","raw_affiliation_strings":["Computer Center, Peking University, Beijing, China"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Computer Center, Peking University, Beijing, China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5036145324"],"corresponding_institution_ids":["https://openalex.org/I125839683"],"apc_list":{"value":1850,"currency":"USD","value_usd":1850},"apc_paid":{"value":1850,"currency":"USD","value_usd":1850},"fwci":8.9197,"has_fulltext":false,"cited_by_count":52,"citation_normalized_percentile":{"value":0.97573788,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":99},"biblio":{"volume":"6","issue":null,"first_page":"60264","last_page":"60273"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T11122","display_name":"Online Learning and Analytics","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1706","display_name":"Computer Science Applications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T12127","display_name":"Software System Performance and Reliability","score":0.9904000163078308,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11652","display_name":"Imbalanced Data Classification Techniques","score":0.9480000138282776,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7728561162948608},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.7289648652076721},{"id":"https://openalex.org/keywords/perceptron","display_name":"Perceptron","score":0.6077418327331543},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5493438243865967},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.548126220703125},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.522284746170044},{"id":"https://openalex.org/keywords/multilayer-perceptron","display_name":"Multilayer perceptron","score":0.5082166194915771},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.44955405592918396},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.4283856749534607},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.2896420359611511}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7728561162948608},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.7289648652076721},{"id":"https://openalex.org/C60908668","wikidata":"https://www.wikidata.org/wiki/Q690207","display_name":"Perceptron","level":3,"score":0.6077418327331543},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5493438243865967},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.548126220703125},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.522284746170044},{"id":"https://openalex.org/C179717631","wikidata":"https://www.wikidata.org/wiki/Q2991667","display_name":"Multilayer perceptron","level":3,"score":0.5082166194915771},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.44955405592918396},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.4283856749534607},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.2896420359611511}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/access.2018.2875742","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2875742","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:8a260397915e41658ea4564a1647974b","is_oa":true,"landing_page_url":"https://doaj.org/article/8a260397915e41658ea4564a1647974b","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"IEEE Access, Vol 6, Pp 60264-60273 (2018)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1109/access.2018.2875742","is_oa":true,"landing_page_url":"https://doi.org/10.1109/access.2018.2875742","pdf_url":null,"source":{"id":"https://openalex.org/S2485537415","display_name":"IEEE Access","issn_l":"2169-3536","issn":["2169-3536"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Access","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":20,"referenced_works":["https://openalex.org/W1574903860","https://openalex.org/W2044469685","https://openalex.org/W2053503869","https://openalex.org/W2103052024","https://openalex.org/W2106895292","https://openalex.org/W2113331937","https://openalex.org/W2133174524","https://openalex.org/W2156997719","https://openalex.org/W2373555655","https://openalex.org/W2481573984","https://openalex.org/W2505736237","https://openalex.org/W2562878095","https://openalex.org/W2572386335","https://openalex.org/W2617300785","https://openalex.org/W2773952019","https://openalex.org/W2774448381","https://openalex.org/W2795304059","https://openalex.org/W6676873227","https://openalex.org/W6683142970","https://openalex.org/W6731089109"],"related_works":["https://openalex.org/W2076543106","https://openalex.org/W2523437662","https://openalex.org/W89844371","https://openalex.org/W2019891950","https://openalex.org/W2085842814","https://openalex.org/W4286643620","https://openalex.org/W4387048144","https://openalex.org/W2492135063","https://openalex.org/W2362514456","https://openalex.org/W2136232598"],"abstract_inverted_index":{"Isolate":[0],"data":[1,15,41,49,51,53,62,64],"among":[2,12],"different":[3],"campus":[4],"information":[5,11],"systems":[6,19],"and":[7,43,55,105],"not":[8],"much":[9],"effective":[10],"the":[13,48,76,92],"big":[14],"generated":[16],"by":[17],"these":[18,61],"cause":[20],"that":[21],"it":[22],"is":[23],"a":[24,34,68,110],"challenge":[25],"for":[26],"predicting":[27,37],"achievement":[28,36,45,77,96],"of":[29,78,88,94],"students.":[30,79],"This":[31],"paper":[32],"designs":[33],"student":[35,44,95],"framework,":[38],"which":[39],"includes":[40],"processing":[42],"predicting.":[46],"In":[47],"processing,":[50],"extraction,":[52],"cleaning,":[54],"feature":[56],"extraction":[57],"are":[58,81],"designed.":[59],"Using":[60],"in":[63],"warehouse,":[65],"we":[66],"propose":[67],"layer-supervised":[69],"multi-layer":[70],"perceptron":[71],"(MLP)-based":[72],"method":[73,108],"to":[74,83,90],"predict":[75],"Supervisions":[80],"fed":[82],"each":[84],"corresponding":[85],"hidden":[86],"layer":[87],"MLP":[89],"improve":[91],"performance":[93],"prediction.":[97],"Compared":[98],"with":[99],"SVM,":[100],"Naive":[101],"Bayes,":[102],"logistic":[103],"regression,":[104],"MLP,":[106],"our":[107],"gets":[109],"better":[111],"performance.":[112]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":14},{"year":2021,"cited_by_count":15},{"year":2020,"cited_by_count":7},{"year":2019,"cited_by_count":5}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}