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Volumn 21, Issue 2, 2010, Pages 327-343

Predicting labels for dyadic data

Author keywords

Collaborative filtering; Dyadic prediction; Link prediction; Relational learning; Social networks; Within network classification

Indexed keywords

COLLABORATIVE FILTERING; DYADIC PREDICTION; LINK PREDICTION; NETWORK CLASSIFICATION; RELATIONAL LEARNING; SOCIAL NETWORKS;

EID: 77958056227     PISSN: 13845810     EISSN: None     Source Type: Journal    
DOI: 10.1007/s10618-010-0189-3     Document Type: Conference Paper
Times cited : (27)

References (14)
  • 3
    • 27544435556 scopus 로고    scopus 로고
    • Link prediction approach to collaborative filtering
    • (Denver, CO, USA, June 7-11, 2005), JCDL'05. ACM, New York, NY
    • Huang Z, Li X, Chen H (2005) Link prediction approach to collaborative filtering. In: Proceedings of the 5th ACM/IEEE-CS joint conference on digital libraries (Denver, CO, USA, June 7-11, 2005), JCDL'05. ACM, New York, NY, pp 141-142
    • (2005) Proceedings of the 5th ACM/IEEE-CS Joint Conference On Digital Libraries , pp. 141-142
    • Huang, Z.1    Li, X.2    Chen, H.3
  • 7
    • 58549116699 scopus 로고    scopus 로고
    • Dynamic network model for predicting occurrences of salmonella at food facilities
    • Springer, Heidelberg
    • Sarkar P, Chen L, Dubrawski A (2008) Dynamic network model for predicting occurrences of salmonella at food facilities. In: Proceedings of the BioSecure international workshop. Springer, Heidelberg, pp 56-63
    • (2008) Proceedings of the Bio Secure International Workshop , pp. 56-63
    • Sarkar, P.1    Chen, L.2    Dubrawski, A.3
  • 10
    • 77958026250 scopus 로고    scopus 로고
    • USPS. Obtained from
    • USPS (2010) USPS dataset. Obtained from http://www-i6.informatik.rwth- aachen.de/~keysers/usps.html
    • (2010) USPS Dataset


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.