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Volumn 474, Issue , 2009, Pages

Materializing and querying learned knowledge

Author keywords

[No Author keywords available]

Indexed keywords

HIGH-DIMENSIONAL; LEARNING APPROACH; LOADING TIME; LOGICAL REASONING; MISSING DATA; TRUTH VALUES; TYPICAL PROPERTIES; USER INTERVENTION;

EID: 84887239727     PISSN: 16130073     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (19)

References (29)
  • 4
    • 53349100683 scopus 로고    scopus 로고
    • Markov logic: A unifying framework for statistical relational learning
    • Getoor, L. Taskar, B. eds.:, MIT Press
    • Domingos, P., Richardson, M.: Markov logic: A unifying framework for statistical relational learning. In Getoor, L., Taskar, B., eds.: Introduction to Statistical Relational Learning. MIT Press (2007).
    • (2007) Introduction to Statistical Relational Learning
    • Domingos, P.1    Richardson, M.2
  • 7
    • 0001172265 scopus 로고
    • Learning logical definitions from relations
    • Quinlan, J.R.: Learning logical definitions from relations. Machine Learning 5(3) (1990).
    • (1990) Machine Learning , vol.5 , Issue.3
    • Quinlan, J.R.1
  • 12
    • 70349957476 scopus 로고    scopus 로고
    • Adding data mining support to sparql via statistical relational learning methods
    • Springer-Verlag
    • Kiefer, C., Bernstein, A., Locher, A.: Adding data mining support to sparql via statistical relational learning methods. In: ESWC 2008, Springer-Verlag (2008).
    • (2008) ESWC 2008
    • Kiefer, C.1    Bernstein, A.2    Locher, A.3
  • 19
    • 84887224222 scopus 로고    scopus 로고
    • Machine learning and the semantic web
    • Staab, S., Hotho, A.: Machine learning and the semantic web. In: ICML 2005 tutorial. (2005).
    • (2005) ICML 2005 Tutorial
    • Staab, S.1    Hotho, A.2
  • 21
    • 58449132042 scopus 로고    scopus 로고
    • The challenges of the semantic web to machine learning and data mining
    • Tutor
    • Lisi, F.A.: The challenges of the semantic web to machine learning and data mining. In: Tutorial at ECML 2006. (2006).
    • (2006) Ial at ECML 2006
    • Lisi, F.A.1
  • 22
    • 1942515438 scopus 로고    scopus 로고
    • From propositional to relational data mining
    • Dzeroski, S. Lavrac, L. eds.:, Springer-Verlag
    • Kramer, S., Lavrac, N., Flach, P.: From propositional to relational data mining. In Dzeroski, S., Lavrac, L., eds.: Relational Data Mining. Springer-Verlag (2001).
    • (2001) Relational Data Mining
    • Kramer, S.1    Lavrac, N.2    Flach, P.3
  • 23
    • 58449119908 scopus 로고    scopus 로고
    • Feature generation and selection in multi-relational statistical learning
    • Getoor, L. Taskar, B. eds.:, MIT Press
    • Popescul, A., Ungar, L.H.: Feature generation and selection in multi-relational statistical learning. In Getoor, L., Taskar, B., eds.: Introduction to Statistical Relational Learning. MIT Press (2007).
    • (2007) Introduction to Statistical Relational Learning
    • Popescul, A.1    Ungar, L.H.2
  • 24
    • 84860846783 scopus 로고    scopus 로고
    • Closed world reasoning in the semantic web through epistemic operators
    • Grimm, S., Motik, B.: Closed world reasoning in the semantic web through epistemic operators. In: OWLED. (2005).
    • (2005) OWLED
    • Grimm, S.1    Motik, B.2
  • 25
    • 0033592606 scopus 로고    scopus 로고
    • Learning the parts of objects by non-negative matrix factorization
    • Lee, D.D., Seung, H.S.: Learning the parts of objects by non-negative matrix factorization. Nature (1999).
    • (1999) Nature
    • Lee, D.D.1    Seung, H.S.2
  • 28
    • 0033645041 scopus 로고    scopus 로고
    • IR evaluation methods for retrieving highly relevant documents
    • In
    • Jarvelin, K., Kekalainen, J.: IR evaluation methods for retrieving highly relevant documents. In: SIGIR'00. (2000).
    • (2000) SIGIR'00
    • Jarvelin, K.1    Kekalainen, J.2


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.