Development of Spectral Clustering Algorithm in Cognitive Diagnosis Model: Approach for Student’s Psychological Growth

With the development of intelligent education, the diagnostic performance of the traditional cognitive diagnostic model has been unable to meet the needs of today’s education. This study uses the Gaussian mixture model (GMM) to model and optimize model parameters through maximum probability estimati...

Celý popis

Uložené v:
Podrobná bibliografia
Vydané v:International journal of computational intelligence systems Ročník 18; číslo 1; s. 211 - 15
Hlavný autor: Chang, Xiao
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: Dordrecht Springer Netherlands 18.08.2025
Springer Nature B.V
Springer
Predmet:
Algorithms
Artificial Intelligence
Cluster analysis
Clustering
Cognition & reasoning
Cognitive ability
Cognitive diagnosis
Computational Intelligence
Control
Datasets
Diagnosis
Education
Engineering
Gaussian mixture model
Graph segmentation
Information technology
Mathematical Logic and Foundations
Mechatronics
Methods
Optimization
Probabilistic models
Psychological development
Research Article
Robotics
Spectral clustering algorithm
Students
Psychological development
Spectral clustering algorithm
Cognitive diagnosis
Gaussian mixture model
Graph segmentation
ISSN:1875-6883, 1875-6891, 1875-6883
On-line prístup:Získať plný text
Tagy: Pridať tag
Žiadne tagy, Buďte prvý, kto otaguje tento záznam!
Abstract With the development of intelligent education, the diagnostic performance of the traditional cognitive diagnostic model has been unable to meet the needs of today’s education. This study uses the Gaussian mixture model (GMM) to model and optimize model parameters through maximum probability estimation. The spectral clustering (SC) algorithm iterative optimization was combined with a similarity matrix and Laplacian matrix to construct an improved spectral clustering cognitive diagnosis model. The proposed SC algorithm’s clustering accuracy was 0.95, ARI was 0.86, and FMI was 0.85, and its clustering performance was better than that of other comparison algorithms. The cognitive diagnosis model based on the SC algorithm showed 4.01 SC, and the psychological status score was 3.97. The clustering performance of the model proposed in this study showed a favorable outcome. Moreover, the cognitive diagnosis model based on SC can meet the cognitive diagnosis needs of most students and help improve their cognitive ability. The enhanced cognitive diagnostic model combining SC and the GMM proposed has significant advantages in clustering performance and educational application effects, providing technical support for promoting students’ psychological growth.
AbstractList Abstract With the development of intelligent education, the diagnostic performance of the traditional cognitive diagnostic model has been unable to meet the needs of today’s education. This study uses the Gaussian mixture model (GMM) to model and optimize model parameters through maximum probability estimation. The spectral clustering (SC) algorithm iterative optimization was combined with a similarity matrix and Laplacian matrix to construct an improved spectral clustering cognitive diagnosis model. The proposed SC algorithm’s clustering accuracy was 0.95, ARI was 0.86, and FMI was 0.85, and its clustering performance was better than that of other comparison algorithms. The cognitive diagnosis model based on the SC algorithm showed 4.01 SC, and the psychological status score was 3.97. The clustering performance of the model proposed in this study showed a favorable outcome. Moreover, the cognitive diagnosis model based on SC can meet the cognitive diagnosis needs of most students and help improve their cognitive ability. The enhanced cognitive diagnostic model combining SC and the GMM proposed has significant advantages in clustering performance and educational application effects, providing technical support for promoting students’ psychological growth.
With the development of intelligent education, the diagnostic performance of the traditional cognitive diagnostic model has been unable to meet the needs of today’s education. This study uses the Gaussian mixture model (GMM) to model and optimize model parameters through maximum probability estimation. The spectral clustering (SC) algorithm iterative optimization was combined with a similarity matrix and Laplacian matrix to construct an improved spectral clustering cognitive diagnosis model. The proposed SC algorithm’s clustering accuracy was 0.95, ARI was 0.86, and FMI was 0.85, and its clustering performance was better than that of other comparison algorithms. The cognitive diagnosis model based on the SC algorithm showed 4.01 SC, and the psychological status score was 3.97. The clustering performance of the model proposed in this study showed a favorable outcome. Moreover, the cognitive diagnosis model based on SC can meet the cognitive diagnosis needs of most students and help improve their cognitive ability. The enhanced cognitive diagnostic model combining SC and the GMM proposed has significant advantages in clustering performance and educational application effects, providing technical support for promoting students’ psychological growth.
ArticleNumber 211
Author Chang, Xiao
Author_xml – sequence: 1
  givenname: Xiao
  surname: Chang
  fullname: Chang, Xiao
  email: sarahcxcx@163.com
  organization: Faculty of Foreign Languages, Huaiyin Institute of Technology
BookMark eNp9kc1u1DAUhSNUJErpC7CyxDpw_Z-wG01pqVQEUmFteZybjEeZONieDt3xGrweT4LbIGDFytbROZ_v9XlenUxhwqp6SeE1BdBvkhC0VTUwWQM0oq2PT6pT2mhZq6bhJ__cn1XnKe0AgFEBIMRp9e0C73AM8x6nTEJPbmd0OdqRrMdDyhj9NJDVOITo83ZP_ETWYZh89ndILrwdppB8Ih9Ch-NbsprnGKzbkj5EcpsPXWH-_P4jkU_p3m3DGAbvCvkqhmPevqie9nZMeP77PKu-XL77vH5f33y8ul6vbmrHG5ZrblvqNj2lGjXHruedhF5ikQXTqpPYUC42LWw4SgfCCgutVtxq6KxA3fGz6nrhdsHuzBz93sZ7E6w3j0KIg7ExezeiUW2LwFrVSNkLq10DmnHZOLHpmaKcFdarhVX2_HrAlM0uHOJUxjecKS2KScniYovLxZBSxP7PqxTMQ2FmKcyUwsxjYeZYQnwJpfnhzzH-Rf8n9Qsl95xQ
Cites_doi 10.1007/s00701-020-04479-3
10.1002/pon.5390
10.1021/acs.jpcc.0c11473
10.1111/1440-1630.12617
10.1002/int.22319
10.1109/TPWRD.2019.2915342
10.1111/ejn.15423
10.1016/j.neucom.2022.04.030
10.1016/j.patrec.2020.08.020
10.1017/S1355617720000272
10.1016/j.neucom.2021.09.052
10.1109/LSP.2019.2961071
10.1038/s41440-021-00704-3
10.1109/TR.2021.3079955
10.1097/WAD.0000000000000379
10.23919/JCC.2020.04.013
ContentType Journal Article
Copyright The Author(s) 2025
The Author(s) 2025. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
Copyright_xml – notice: The Author(s) 2025
– notice: The Author(s) 2025. This work is published under http://creativecommons.org/licenses/by-nc-nd/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.
DBID C6C
AAYXX
CITATION
7SC
8FD
8FE
8FG
AFKRA
ARAPS
AZQEC
BENPR
BGLVJ
CCPQU
DWQXO
GNUQQ
HCIFZ
JQ2
K7-
L7M
L~C
L~D
P62
PHGZM
PHGZT
PKEHL
PQEST
PQGLB
PQQKQ
PQUKI
PRINS
DOA
DOI 10.1007/s44196-025-00849-w
DatabaseName Springer Nature OA Free Journals
CrossRef
Computer and Information Systems Abstracts
Technology Research Database
ProQuest SciTech Collection
ProQuest Technology Collection
ProQuest Central UK/Ireland
ProQuest SciTech Premium Collection Technology Collection Advanced Technologies & Aerospace Collection
ProQuest Central Essentials
ProQuest Central
ProQuest Technology Collection
ProQuest One Community College
ProQuest Central Korea
ProQuest Central Student
SciTech Premium Collection
ProQuest Computer Science Collection
Computer Science Database
Advanced Technologies Database with Aerospace
Computer and Information Systems Abstracts – Academic
Computer and Information Systems Abstracts Professional
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Premium
ProQuest One Academic (New)
ProQuest One Academic Middle East (New)
ProQuest One Academic Eastern Edition (DO NOT USE)
ProQuest One Applied & Life Sciences
ProQuest One Academic (retired)
ProQuest One Academic UKI Edition
ProQuest Central China
DOAJ Directory of Open Access Journals
DatabaseTitle CrossRef
Computer Science Database
ProQuest Central Student
Technology Collection
Technology Research Database
Computer and Information Systems Abstracts – Academic
ProQuest One Academic Middle East (New)
ProQuest Advanced Technologies & Aerospace Collection
ProQuest Central Essentials
ProQuest Computer Science Collection
Computer and Information Systems Abstracts
SciTech Premium Collection
ProQuest One Community College
ProQuest Central China
ProQuest Central
ProQuest One Applied & Life Sciences
ProQuest Central Korea
ProQuest Central (New)
Advanced Technologies Database with Aerospace
Advanced Technologies & Aerospace Collection
ProQuest One Academic Eastern Edition
ProQuest Technology Collection
ProQuest SciTech Collection
Computer and Information Systems Abstracts Professional
ProQuest One Academic UKI Edition
ProQuest One Academic
ProQuest One Academic (New)
DatabaseTitleList
Computer Science Database
Database_xml – sequence: 1
  dbid: DOA
  name: DOAJ Directory of Open Access Journals
  url: https://www.doaj.org/
  sourceTypes: Open Website
– sequence: 2
  dbid: BENPR
  name: ProQuest Central
  url: https://www.proquest.com/central
  sourceTypes: Aggregation Database
DeliveryMethod fulltext_linktorsrc
Discipline Engineering
Computer Science
Education
EISSN 1875-6883
EndPage 15
ExternalDocumentID oai_doaj_org_article_699e0296855f4a7c8072358c4bf26132
10_1007_s44196_025_00849_w
GrantInformation_xml – fundername: Research on Teaching Chinese as a Foreign Language Syntactic from the Perspective of Dynamic Syntax
GroupedDBID 0R~
4.4
5GY
AAFWJ
AAJSJ
AAKKN
AASML
ABEEZ
ABFIM
ACACY
ACGFS
ACULB
ADBBV
ADCVX
AENEX
AFGXO
AFPKN
ALMA_UNASSIGNED_HOLDINGS
ARCSS
AVBZW
BCNDV
C24
C6C
CS3
DU5
EBLON
EBS
EJD
GROUPED_DOAJ
GTTXZ
HZ~
J~4
O9-
OK1
SOJ
TFW
TR2
AAYXX
AFFHD
AFKRA
ARAPS
BENPR
BGLVJ
CCPQU
CITATION
HCIFZ
K7-
PHGZM
PHGZT
PQGLB
7SC
8FD
8FE
8FG
AZQEC
DWQXO
GNUQQ
JQ2
L7M
L~C
L~D
P62
PKEHL
PQEST
PQQKQ
PQUKI
PRINS
ID FETCH-LOGICAL-c382t-3a91cbf117e73edf3d50f5e3a94276d5e8134b90b3e5c04a4a09763a70da4e7d3
IEDL.DBID K7-
ISICitedReferencesCount 0
ISICitedReferencesURI http://www.webofscience.com/api/gateway?GWVersion=2&SrcApp=Summon&SrcAuth=ProQuest&DestLinkType=CitingArticles&DestApp=WOS_CPL&KeyUT=001552049900002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
ISSN 1875-6883
1875-6891
IngestDate Fri Oct 03 12:26:09 EDT 2025
Sat Nov 01 15:17:23 EDT 2025
Sat Nov 29 07:30:52 EST 2025
Tue Aug 19 01:10:47 EDT 2025
IsDoiOpenAccess true
IsOpenAccess true
IsPeerReviewed true
IsScholarly true
Issue 1
Keywords Psychological development
Spectral clustering algorithm
Cognitive diagnosis
Gaussian mixture model
Graph segmentation
Language English
LinkModel DirectLink
MergedId FETCHMERGED-LOGICAL-c382t-3a91cbf117e73edf3d50f5e3a94276d5e8134b90b3e5c04a4a09763a70da4e7d3
Notes ObjectType-Article-1
SourceType-Scholarly Journals-1
ObjectType-Feature-2
content type line 14
OpenAccessLink https://doaj.org/article/699e0296855f4a7c8072358c4bf26132
PQID 3267461365
PQPubID 4869256
PageCount 15
ParticipantIDs doaj_primary_oai_doaj_org_article_699e0296855f4a7c8072358c4bf26132
proquest_journals_3267461365
crossref_primary_10_1007_s44196_025_00849_w
springer_journals_10_1007_s44196_025_00849_w
PublicationCentury 2000
PublicationDate 2025-08-18
PublicationDateYYYYMMDD 2025-08-18
PublicationDate_xml – month: 08
  year: 2025
  text: 2025-08-18
  day: 18
PublicationDecade 2020
PublicationPlace Dordrecht
PublicationPlace_xml – name: Dordrecht
– name: Abingdon
PublicationTitle International journal of computational intelligence systems
PublicationTitleAbbrev Int J Comput Intell Syst
PublicationYear 2025
Publisher Springer Netherlands
Springer Nature B.V
Springer
Publisher_xml – name: Springer Netherlands
– name: Springer Nature B.V
– name: Springer
References A Li (849_CR9) 2021; 70
PA Ejegwa (849_CR16) 2023; 2
KJ Harper (849_CR1) 2020; 67
A Gibson (849_CR13) 2020; 3
M Wibroe (849_CR15) 2021; 163
HW Yeung (849_CR10) 2021; 6
NM Payton (849_CR3) 2020; 26
J Qin (849_CR12) 2021; 10
Y Cai (849_CR7) 2022; 493
G Perera (849_CR14) 2020; 2
M Betchen (849_CR17) 2020; 29
CH Hung (849_CR2) 2020; 120
L Lin (849_CR11) 2021; 125
G Liu (849_CR18) 2020; 17
TJ Park (849_CR19) 2020; 27
Y Zhao (849_CR8) 2022; 468
X Yu (849_CR4) 2020; 36
A Sellami (849_CR20) 2020; 138
J Wang (849_CR6) 2020; 383
M Dabbaghjamanesh (849_CR5) 2020; 35
References_xml – volume: 163
  start-page: 1291
  issue: 5
  year: 2021
  ident: 849_CR15
  publication-title: Acta Neurochir.
  doi: 10.1007/s00701-020-04479-3
– volume: 29
  start-page: 1148
  issue: 7
  year: 2020
  ident: 849_CR17
  publication-title: Psychooncology
  doi: 10.1002/pon.5390
– volume: 125
  start-page: 2623
  issue: 6
  year: 2021
  ident: 849_CR11
  publication-title: J. Phys. Chem. C
  doi: 10.1021/acs.jpcc.0c11473
– volume: 67
  start-page: 13
  issue: 1
  year: 2020
  ident: 849_CR1
  publication-title: Aust. Occup. Ther. J.
  doi: 10.1111/1440-1630.12617
– volume: 36
  start-page: 757
  issue: 2
  year: 2020
  ident: 849_CR4
  publication-title: Int. J. Intell. Syst.
  doi: 10.1002/int.22319
– volume: 2
  start-page: 271
  issue: 36
  year: 2020
  ident: 849_CR14
  publication-title: Int. J. Geriatr. Psychiatry
– volume: 35
  start-page: 560
  issue: 2
  year: 2020
  ident: 849_CR5
  publication-title: IEEE Trans. Power Deliv.
  doi: 10.1109/TPWRD.2019.2915342
– volume: 6
  start-page: 6281
  issue: 54
  year: 2021
  ident: 849_CR10
  publication-title: Eur. J. Neurosci.
  doi: 10.1111/ejn.15423
– volume: 2
  start-page: 68
  issue: 1
  year: 2023
  ident: 849_CR16
  publication-title: J. Comput. Cogn. Eng.
– volume: 383
  start-page: 10
  issue: 28
  year: 2020
  ident: 849_CR6
  publication-title: Neurocomputing
– volume: 493
  start-page: 191
  issue: 7
  year: 2022
  ident: 849_CR7
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2022.04.030
– volume: 138
  start-page: 594
  issue: 10
  year: 2020
  ident: 849_CR20
  publication-title: Pattern Recogn. Lett.
  doi: 10.1016/j.patrec.2020.08.020
– volume: 26
  start-page: 1
  issue: 8
  year: 2020
  ident: 849_CR3
  publication-title: J. InT. Neuropsychol. Soc.
  doi: 10.1017/S1355617720000272
– volume: 468
  start-page: 257
  issue: 11
  year: 2022
  ident: 849_CR8
  publication-title: Neurocomputing
  doi: 10.1016/j.neucom.2021.09.052
– volume: 120
  start-page: 533
  issue: 2
  year: 2020
  ident: 849_CR2
  publication-title: J. Formos. Med. Assoc.
– volume: 27
  start-page: 381
  issue: 1
  year: 2020
  ident: 849_CR19
  publication-title: IEEE Signal Process. Lett.
  doi: 10.1109/LSP.2019.2961071
– volume: 10
  start-page: 1251
  issue: 44
  year: 2021
  ident: 849_CR12
  publication-title: Hypertens. Res.
  doi: 10.1038/s41440-021-00704-3
– volume: 70
  start-page: 916
  issue: 3
  year: 2021
  ident: 849_CR9
  publication-title: IEEE Trans. Reliability
  doi: 10.1109/TR.2021.3079955
– volume: 3
  start-page: 262
  issue: 34
  year: 2020
  ident: 849_CR13
  publication-title: Alzheimer Dis. Assoc. Disord.
  doi: 10.1097/WAD.0000000000000379
– volume: 17
  start-page: 140
  issue: 4
  year: 2020
  ident: 849_CR18
  publication-title: China Commun.
  doi: 10.23919/JCC.2020.04.013
SSID ssj0002140044
ssib050732782
Score 2.3592503
Snippet With the development of intelligent education, the diagnostic performance of the traditional cognitive diagnostic model has been unable to meet the needs of...
Abstract With the development of intelligent education, the diagnostic performance of the traditional cognitive diagnostic model has been unable to meet the...
SourceID doaj
proquest
crossref
springer
SourceType Open Website
Aggregation Database
Index Database
Publisher
StartPage 211
SubjectTerms Algorithms
Artificial Intelligence
Cluster analysis
Clustering
Cognition & reasoning
Cognitive ability
Cognitive diagnosis
Computational Intelligence
Control
Datasets
Diagnosis
Education
Engineering
Gaussian mixture model
Graph segmentation
Information technology
Mathematical Logic and Foundations
Mechatronics
Methods
Optimization
Probabilistic models
Psychological development
Research Article
Robotics
Spectral clustering algorithm
Students
SummonAdditionalLinks – databaseName: DOAJ Directory of Open Access Journals
  dbid: DOA
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwrV07T8MwELZQxcDCG1EoyAMbRDixHdtspbwmhARIbJaTOFCptKhNKSN_g7_HL-HsJKVFQiyszkOW77Pvu-TuO4QOpJUZRMc0EOA9AsYBxjIxPOBKWaDX3PKU-WYT4vpaPjyom5lWXy4nrJQHLhfuOIaHSKRiyXnOjEglEa66M2VJDuSf-tOXCDUTTLkzOAodNllVJeNr5cDv-3xbHjgNeRVM5jyRF-yfY5k_fox6f3OxipYroojb5QTX0ILtr6OVugkDrvbkBnqbSfvBgxy7hvLu6wXu9MZOBAFejtu9x8GwWzw9424fd-qEIXxWptl1R9h1ROud4HYlMI6ByeLbUvXy8_1jhOeOSXwJoXvxtInuL87vOldB1U4hSKmMioAaFaZJHobCCmqznGac5NzCMItEnHErQ8oSRRIKBiLMMEOAq1AjSGaYFRndQo3-oG-3EQafxhJhwdfLiPHQqNQoI6VV3BqSxUkTHdZLq19K1Qw91Uf2htBgCO0NoSdNdOpWf3qnU7z2A4ADXeFA_4WDJmrVttPVNhxp4KaCxS6Tr4mOant-X_59Sjv_MaVdtBR5vEGcLluoUQzHdg8tpq9FdzTc94D9Ak0n7N0
  priority: 102
  providerName: Directory of Open Access Journals
– databaseName: SpringerLink Open Access Journals
  dbid: C24
  link: http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnV1Nb9QwEB2VlgMc6AcgFtrKh95opCS2Y5vbknbbU1UJkPZmOYmzu9KyizYp5cjf4O_xSxg7zrZblQNcE0eyPM-eN_HMG4ATaWWF0TGNBHqPiHGEsSwMj7hSFuk1t7xkvtmEuLqS47G6DkVhTZ_t3l9J-pN6XeyGjtsnzPLIicCr6PYJ7PBEKpfIl4caB3f-ponDJQsVMo9_uuGFvFj_BsN8cCnqfc1o9_9muQcvArckww4M-7BlFwew2_dtIGEbH8DzeyKEL-HHvbwhsqyJ60jvfn-QfH7jVBRwEBnOJ8vVrJ1-JbMFyfuMI3LW5enNGuJaqs0_kGFQKCdIhcmnTjbz989fDdk4Z8kFxv7t9BV8GZ1_zi-j0I8hKqlM24galZRFnSTCCmqrmlY8rrnFxywVWcWtTCgrVFxQtHDMDDMxkh1qRFwZZkVFX8P2Yrmwb4CgU2SFsEgWZMp4YlRplJHSKm5NXGXFAN739tHfOtkNvRZY9kuscYm1X2J9O4CPzoTrkU4y2z9YriY67ECdIfriVGWS85oZUcpYuDLhkhU1RpE0HcBhDwAd9nGjkdwKlrlUwAGc9ga_e_33Kb39t-Hv4FnqMYMhvTyE7XZ1Y4_gafm9nTWrY4_vP-0z92Y
  priority: 102
  providerName: Springer Nature
Title Development of Spectral Clustering Algorithm in Cognitive Diagnosis Model: Approach for Student’s Psychological Growth
URI https://link.springer.com/article/10.1007/s44196-025-00849-w
https://www.proquest.com/docview/3267461365
https://doaj.org/article/699e0296855f4a7c8072358c4bf26132
Volume 18
WOSCitedRecordID wos001552049900002&url=https%3A%2F%2Fcvtisr.summon.serialssolutions.com%2F%23%21%2Fsearch%3Fho%3Df%26include.ft.matches%3Dt%26l%3Dnull%26q%3D
hasFullText 1
inHoldings 1
isFullTextHit
isPrint
journalDatabaseRights – providerCode: PRVAON
  databaseName: DOAJ Directory of Open Access Journals
  customDbUrl:
  eissn: 1875-6883
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002140044
  issn: 1875-6883
  databaseCode: DOA
  dateStart: 20080101
  isFulltext: true
  titleUrlDefault: https://www.doaj.org/
  providerName: Directory of Open Access Journals
– providerCode: PRVHPJ
  databaseName: ROAD: Directory of Open Access Scholarly Resources
  customDbUrl:
  eissn: 1875-6883
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssib050732782
  issn: 1875-6883
  databaseCode: M~E
  dateStart: 20120101
  isFulltext: true
  titleUrlDefault: https://road.issn.org
  providerName: ISSN International Centre
– providerCode: PRVPQU
  databaseName: Computer Science Database
  customDbUrl:
  eissn: 1875-6883
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002140044
  issn: 1875-6883
  databaseCode: K7-
  dateStart: 20140101
  isFulltext: true
  titleUrlDefault: http://search.proquest.com/compscijour
  providerName: ProQuest
– providerCode: PRVPQU
  databaseName: ProQuest Central
  customDbUrl:
  eissn: 1875-6883
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002140044
  issn: 1875-6883
  databaseCode: BENPR
  dateStart: 20140101
  isFulltext: true
  titleUrlDefault: https://www.proquest.com/central
  providerName: ProQuest
– providerCode: PRVAVX
  databaseName: Springer Nature OA Free Journals
  customDbUrl:
  eissn: 1875-6883
  dateEnd: 99991231
  omitProxy: false
  ssIdentifier: ssj0002140044
  issn: 1875-6883
  databaseCode: C24
  dateStart: 20211201
  isFulltext: true
  titleUrlDefault: https://link.springer.com/search?facet-content-type=%22Journal%22
  providerName: Springer Nature
link http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lb9QwEB7RlgMXWgqIpWXlAzewSPyIbS7VdtvCaVXxkHqLnMRpV9puyiZlOfI3-vf6Sxh7nZZFggvXJEoczevzzPgbgNfa6Qp3x5wqjB5USFRjXVhJpTEO4bV0shRh2ISaTPTZmTmNCbc2tlX2PjE46qopfY78HcIMJTLflHVw9Y36qVG-uhpHaGzAVsrQCfuirKK9PiHU4axna_eemaVeY0OhGWE6zbRJ4zmacJoOkUHoyJXUs8wbulyLVYHSfw2H_lE6DRHpZPt__2UHHkcsSkYr5XkCD9x8F7b7OQ8kmv2un-wcu0Cewo_fuoxIUxM_v94nS8h4du05F3ClZDQ7x691F5dkOifjvj-JHK26-qYt8QPYZu_JKPKZEwTO5POKZPP2501L1rwy-bBolt3FM_h6cvxl_JHG6Q205Jp1lFuTlkWdpsop7qqaVzKppcPLgqmskk6nXBQmKTjqQyKssAlCI25VUlnhVMWfw-a8mbsXQDCEikI5hBaaCZlaU1pjtXZGOptUWTGAN72c8qsVSUd-R8ccpJqjVPMg1Xw5gEMvyrsnPcF2uNAszvNor3mGupowk2kpa2FVqRPlDxWXoqhxz8nZAPZ70ebR6tv8Xq4DeNsrx_3tvy_p5b_ftgePWFBL3PDrfdjsFtfuFTwsv3fTdjGErcPjyemnIWyMmRiGpMIw2MEvjGUI5w
linkProvider ProQuest
linkToHtml http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMw1V3NbtQwELZKQYILhQJioYAPcAKLxD-xjYTQsqW02rJCapF6S53EaVdaNiVJWbjxGrwED8WTMHbilkWCWw9ck5WVON_MfLOe-Qahx8qqArJjRiRED8IFwFhlRhChtQV6LazIuR82IScTdXCg36-gH6EXxpVVBp_oHXVR5e4_8udAMyRPXFHWq5NPxE2NcqerYYRGB4ux_bqAlK15ubMJ3_cJpVtv9kfbpJ8qQHKmaEuY0XGelXEsrWS2KFkholJYuMypTAphVcx4pqOMwXNG3HATQchmRkaF4VYWDNa9hC5zpqSzq7EkAb9ArRgN6vAuEtDYWYg_2Ia0gCRKx33fju_eAybiK4AFcar2miyWYqMfIbDEe_84qvURcGvtf9u7G-h6z7XxsDOOm2jFztfRWphjgXu3tu4mV_dVLrfQl9-qqHBV4j3XiVrDKqPZqdOUgJ3Bw9kRvF17_BFP53gU6q_wZle1OG2wGzA3e4GHvV47hsQA73Uioj-_fW_wUtTBb-tq0R7fRh8uZC_uoNV5Nbd3EQaKwDNpgTopykVsdG60UcpqYU1UJNkAPQ24SE86EZL0TG7aoygFFKUeReligF476Jz90gmI-wtVfZT2_ihNwBYjqhMlRMmNzFUkXdN0zrMScmpGB2gjQCntvVqTnuNogJ4FMJ7f_vsj3fv3ao_Q1e39d7vp7s5kfB9do94kFInVBlpt61P7AF3JP7fTpn7o7Q2jw4sG6S8mGWKt
linkToPdf http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3BbtQwEB2VFiE40FJAXSjUB24QNYnt2Oa2bNlSFa0qAVJvlpM47UpLUmXTLkd-g9_jSxg7ybKLygFxdWzJ8jx7nuOZNwCvpJU53o5pINB7BIwjjGVqeMCVskivueUZ88UmxGQiz8_V2UoWv492758k25wGp9JUNodXeXG4THxDJ-6DZ3ngBOFVsLgDW-5FymF81OU7uLM4jhxGWZctc_vQNY_khfvX2OYfD6Te74y3_3_GO_Cw45xk2ILkEWzYche2-3oOpNveu_BgRZzwMXxbiSciVUFcpXr3W4SMZtdOXQE7keHsoqqnzeVXMi3JqI9EIkdt_N50TlyptdlbMuyUywlSZPKpldP8-f3HnKydv-S4rhbN5RP4Mn7_efQh6Oo0BBmVcRNQo6IsLaJIWEFtXtCchwW32MxikeTcyoiyVIUpRcuHzDATIgmiRoS5YVbk9ClsllVp94Cgs2SpsEgiZMx4ZFRmlJHSKm5NmCfpAF73ttJXrRyHXgov-yXWuMTaL7FeDOCdM-eyp5PS9g1VfaG7nakTRGUYq0RyXjAjMhkKlz6csbTA2yWNB7Dfg0F3-3uukfQKlrgQwQG86Y3_-_Pfp_Ts37ofwL2zo7H-eDI5fQ73Yw8fvPXLfdhs6mv7Au5mN810Xr_0sP8FYOMDPg
openUrl ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Development+of+Spectral+Clustering+Algorithm+in+Cognitive+Diagnosis+Model%3A+Approach+for+Student%E2%80%99s+Psychological+Growth&rft.jtitle=International+journal+of+computational+intelligence+systems&rft.au=Chang%2C+Xiao&rft.date=2025-08-18&rft.pub=Springer+Nature+B.V&rft.issn=1875-6891&rft.eissn=1875-6883&rft.volume=18&rft.issue=1&rft.spage=211&rft_id=info:doi/10.1007%2Fs44196-025-00849-w
thumbnail_l http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=1875-6883&client=summon
thumbnail_m http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=1875-6883&client=summon
thumbnail_s http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=1875-6883&client=summon