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Volumn 25, Issue 1, 2012, Pages 51-62

Finding association rules in semantic web data

Author keywords

Association rules; Biomedical application; Data mining; Semantic annotation; Semantic web

Indexed keywords

BIOMEDICAL APPLICATIONS; DATA MINING COMMUNITY; DATA REPOSITORIES; MINING ASSOCIATION RULES; NOVEL METHODS; QUERY PATTERNS; SEMANTIC ANNOTATION; SEMANTIC ANNOTATIONS; SEMANTIC DATA;

EID: 80052417978     PISSN: 09507051     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.knosys.2011.05.009     Document Type: Article
Times cited : (64)

References (41)
  • 1
    • 80052400432 scopus 로고    scopus 로고
    • Workshop on Mining for and from the Semantic Web (MSW-04), 2004
    • Workshop on Mining for and from the Semantic Web (MSW-04), 2004.
  • 2
    • 0027621699 scopus 로고
    • Mining association rules between sets of items in large databases
    • ACM Press
    • R. Agrawal, T. Imielinski, and A.N. Swami Mining association rules between sets of items in large databases SIGMOD Conference 1993 ACM Press pp. 207-216
    • (1993) SIGMOD Conference , pp. 207-216
    • Agrawal, R.1    Imielinski, T.2    Swami, A.N.3
  • 3
    • 29444447081 scopus 로고    scopus 로고
    • An efficient genetic algorithm for automated mining of both positive and negative quantitative association rules
    • DOI 10.1007/s00500-005-0476-x
    • B. Alatas, and E. Akin An efficient genetic algorithm for automated mining of both positive and negative quantitative association rules Soft Comput. 10 3 2006 230 237 (Pubitemid 43008736)
    • (2006) Soft Computing , vol.10 , Issue.3 , pp. 230-237
    • Alatas, B.1    Akin, E.2
  • 4
    • 77949615569 scopus 로고    scopus 로고
    • Analysis of the effectiveness of the genetic algorithms based on extraction of association rules
    • J. Alcala-Fdez, N. Flugy-Pape, A. Bonarini, and F. Herrera Analysis of the effectiveness of the genetic algorithms based on extraction of association rules Fundam. Inf. 98 2010 1 14
    • (2010) Fundam. Inf. , vol.98 , pp. 1-14
    • Alcala-Fdez, J.1    Flugy-Pape, N.2    Bonarini, A.3    Herrera, F.4
  • 5
    • 77249115630 scopus 로고    scopus 로고
    • A document clustering algorithm for discovering and describing topics
    • H. Anaya-Sánchez, A. Pons-Porrata, and R. Berlanga A document clustering algorithm for discovering and describing topics Pattern Recognit. Lett. 31 6 2010 502 510
    • (2010) Pattern Recognit. Lett. , vol.31 , Issue.6 , pp. 502-510
    • Anaya-Sánchez, H.1    Pons-Porrata, A.2    Berlanga, R.3
  • 7
    • 77955227402 scopus 로고    scopus 로고
    • O3R: Ontology-based mechanism for a human-centered environment targeted at the analysis of navigation patterns
    • K. Becker, and M. Vanzin O3R: Ontology-based mechanism for a human-centered environment targeted at the analysis of navigation patterns Know.-Based Syst. 23 2010 455 470
    • (2010) Know.-Based Syst. , vol.23 , pp. 455-470
    • Becker, K.1    Vanzin, M.2
  • 8
    • 49949085013 scopus 로고    scopus 로고
    • Kernel methods for mining instance data in ontologies
    • LNCS Springer
    • S. Bloehdorn, and Y. Sure Kernel methods for mining instance data in ontologies ISWC/ASWC LNCS vol. 4825 2007 Springer 58 71
    • (2007) ISWC/ASWC , vol.4825 , pp. 58-71
    • Bloehdorn, S.1    Sure, Y.2
  • 11
    • 8444227091 scopus 로고    scopus 로고
    • Objectminer: A new approach for mining complex objects
    • R. Dánger, J. Ruiz-Shulcloper, and R.B. Llavori Objectminer: a new approach for mining complex objects ICEIS 2 2004 42 47
    • (2004) ICEIS , vol.2 , pp. 42-47
    • Dánger, R.1    Ruiz-Shulcloper, J.2    Llavori, R.B.3
  • 12
    • 68249093516 scopus 로고    scopus 로고
    • Metric-based stochastic conceptual clustering for ontologies
    • N. Fanizzi, C. d'Amato, and F. Esposito Metric-based stochastic conceptual clustering for ontologies Inf. Syst. 34 8 2009 792 806
    • (2009) Inf. Syst. , vol.34 , Issue.8 , pp. 792-806
    • Fanizzi, N.1    D'Amato, C.2    Esposito, F.3
  • 15
    • 75749141697 scopus 로고    scopus 로고
    • Mining frequent generalized patterns for web personalization in the presence of taxonomies
    • P. Giannikopoulos, I. Varlamis, and M. Eirinaki Mining frequent generalized patterns for web personalization in the presence of taxonomies IJDWM 6 1 2010 58 76
    • (2010) IJDWM , vol.6 , Issue.1 , pp. 58-76
    • Giannikopoulos, P.1    Varlamis, I.2    Eirinaki, M.3
  • 16
    • 27544480125 scopus 로고    scopus 로고
    • Arules - A computational environment for mining association rules and frequent item sets
    • M. Hahsler, B. Gruen, and K. Hornik Arules - a computational environment for mining association rules and frequent item sets J. Stat. Softw. 14 15 2005 1 25
    • (2005) J. Stat. Softw. , vol.14 , Issue.15 , pp. 1-25
    • Hahsler, M.1    Gruen, B.2    Hornik, K.3
  • 18
    • 45449112152 scopus 로고    scopus 로고
    • Adding data mining support to SPARQL via statistical relational learning methods
    • S. Bechhofer, M. Hauswirth, J. Hoffmann, M. Koubarakis, Lecture Notes in Computer Science Springer
    • C. Kiefer, A. Bernstein, and A. Locher Adding data mining support to SPARQL via statistical relational learning methods S. Bechhofer, M. Hauswirth, J. Hoffmann, M. Koubarakis, ESWC Lecture Notes in Computer Science vol. 5021 2008 Springer 478 492
    • (2008) ESWC , vol.5021 , pp. 478-492
    • Kiefer, C.1    Bernstein, A.2    Locher, A.3
  • 20
    • 78149312583 scopus 로고    scopus 로고
    • Frequent subgraph discovery
    • N. Cercone, T.Y. Lin, X. Wu, IEEE Computer Society
    • M. Kuramochi, and G. Karypis Frequent subgraph discovery N. Cercone, T.Y. Lin, X. Wu, ICDM IEEE Computer Society 2001 313 320
    • (2001) ICDM , pp. 313-320
    • Kuramochi, M.1    Karypis, G.2
  • 23
    • 26944490697 scopus 로고    scopus 로고
    • Mining the semantic web: A logic-based methodology
    • LNCS Springer
    • F.A. Lisi, and F. Esposito Mining the semantic web: a logic-based methodology ISMIS LNCS vol. 3488 2005 Springer 102 111
    • (2005) ISMIS , vol.3488 , pp. 102-111
    • Lisi, F.A.1    Esposito, F.2
  • 24
    • 77951766215 scopus 로고    scopus 로고
    • Knowledge-based interactive postmining of association rules using ontologies
    • C. Marinica, and F. Guillet Knowledge-based interactive postmining of association rules using ontologies IEEE Trans. Knowledge Data Eng. 22 6 2010 784 797
    • (2010) IEEE Trans. Knowledge Data Eng. , vol.22 , Issue.6 , pp. 784-797
    • Marinica, C.1    Guillet, F.2
  • 26
    • 0028429573 scopus 로고
    • Inductive logic programming: Theory and methods
    • S. Muggleton, and L.D. Raedt Inductive logic programming: theory and methods J. Log. Program. 19 20 1994 629 679
    • (1994) J. Log. Program. , vol.19 , Issue.20 , pp. 629-679
    • Muggleton, S.1    Raedt, L.D.2
  • 28
    • 80052392272 scopus 로고    scopus 로고
    • Mining association rules from semantic web data
    • V. Nebot, and R. Berlanga Mining association rules from semantic web data Proc. IEA/AIE 2010 0 10
    • (2010) Proc. IEA/AIE , pp. 0-10
    • Nebot, V.1    Berlanga, R.2
  • 29
    • 70349751948 scopus 로고    scopus 로고
    • Efficient retrieval of ontology fragments using an interval labeling scheme
    • V. Nebot, and R.B. Llavori Efficient retrieval of ontology fragments using an interval labeling scheme Inf. Sci. 179 24 2009 4151 4173
    • (2009) Inf. Sci. , vol.179 , Issue.24 , pp. 4151-4173
    • Nebot, V.1    Llavori, R.B.2
  • 30
    • 70350075255 scopus 로고    scopus 로고
    • A relational data harmonization approach to xml
    • T. Niemi, T. Näppilä, and K. Järvelin A relational data harmonization approach to xml J. Inf. Sci. 35 5 2009 571 601
    • (2009) J. Inf. Sci. , vol.35 , Issue.5 , pp. 571-601
    • Niemi, T.1    Näppilä, T.2    Järvelin, K.3
  • 32
    • 0002880407 scopus 로고
    • Mining generalized association rules
    • R. Srikant, and R. Agrawal Mining generalized association rules VLDB 1995 407 419
    • (1995) VLDB , pp. 407-419
    • Srikant, R.1    Agrawal, R.2
  • 33
    • 33744977663 scopus 로고    scopus 로고
    • Semantic Web Mining. State of the art and future directions
    • DOI 10.1016/j.websem.2006.02.001, PII S1570826806000084
    • G. Stumme, A. Hotho, and B. Berendt Semantic web mining: state of the art and future directions Web Semantics: Sci. Services Agents World Wide Web 4 2 2006 124 143 (Pubitemid 43868209)
    • (2006) Web Semantics , vol.4 , Issue.2 , pp. 124-143
    • Stumme, G.1    Hotho, A.2    Berendt, B.3
  • 35
    • 1242308945 scopus 로고    scopus 로고
    • Selecting the right objective measure for association analysis
    • P.-N. Tan, V. Kumar, and J. Srivastava Selecting the right objective measure for association analysis Inf. Syst. 29 2004 293 313
    • (2004) Inf. Syst. , vol.29 , pp. 293-313
    • Tan, P.-N.1    Kumar, V.2    Srivastava, J.3
  • 36
    • 54249093703 scopus 로고    scopus 로고
    • Updating generalized association rules with evolving taxonomies
    • M.-C. Tseng, W.-Y. Lin, and R. Jeng Updating generalized association rules with evolving taxonomies Appl. Intell. 29 3 2008 306 320
    • (2008) Appl. Intell. , vol.29 , Issue.3 , pp. 306-320
    • Tseng, M.-C.1    Lin, W.-Y.2    Jeng, R.3
  • 38
    • 29844451501 scopus 로고    scopus 로고
    • Efficient keyword search for smallest LCAs in XML databases
    • SIGMOD 2005: Proceedings of the ACM SIGMOD International Conference on Management of Data
    • Y. Xu, and Y. Papakonstantinou Efficient keyword search for smallest LCAs in XML databases SIGMOD '05: Proceedings of the 2005 ACM SIGMOD International Conference on Management of Data 2005 ACM New York, NY, USA pp. 527-538 (Pubitemid 43038955)
    • (2005) Proceedings of the ACM SIGMOD International Conference on Management of Data , pp. 527-538
    • Xu, Y.1    Papakonstantinou, Y.2
  • 39
    • 77958008901 scopus 로고    scopus 로고
    • Approximate weighted frequent pattern mining with/without noisy environments
    • U. Yun, and K.H. Ryu Approximate weighted frequent pattern mining with/without noisy environments Know.-Based Syst. 24 2011 73 82
    • (2011) Know.-Based Syst. , vol.24 , pp. 73-82
    • Yun, U.1    Ryu, K.H.2
  • 40
    • 4444337294 scopus 로고    scopus 로고
    • Mining non-redundant association rules
    • DOI 10.1023/B:DAMI.0000040429.96086.c7
    • M.J. Zaki Mining non-redundant association rules Data Min. Knowl. Discov. 9 2004 223 248 (Pubitemid 39193158)
    • (2004) Data Mining and Knowledge Discovery , vol.9 , Issue.3 , pp. 223-248
    • Zaki, M.J.1
  • 41


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.