메뉴 건너뛰기




Volumn , Issue , 2011, Pages 325-333

Interactive learning for efficiently detecting errors in insurance claims

Author keywords

Budgeted learning; Cost sensitive learning; Error detection; Health insurance claims; Interactive machine learning; Quality control

Indexed keywords

BUDGET CONTROL; DATA MINING; HEALTH INSURANCE; LEARNING SYSTEMS; OPERATING COSTS;

EID: 80052669647     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1145/2020408.2020463     Document Type: Conference Paper
Times cited : (18)

References (17)
  • 5
    • 77956221595 scopus 로고    scopus 로고
    • Data mining to predict and prevent errors in health insurance claims processing
    • R. Ghani, M. Kumar, and Z.-S. Mei. Data mining to predict and prevent errors in health insurance claims processing. In Proceedings of KDD, 2010.
    • (2010) Proceedings of KDD
    • Ghani, R.1    Kumar, M.2    Mei, Z.-S.3
  • 9
    • 33749563073 scopus 로고    scopus 로고
    • Training linear svms in linear time
    • T. Joachims. Training linear svms in linear time. In Proceedings of KDD, 2006.
    • (2006) Proceedings of KDD
    • Joachims, T.1
  • 10
    • 50549095275 scopus 로고    scopus 로고
    • Learning and classifying under hard budgets
    • A. Kapoor and R. Greiner. Learning and classifying under hard budgets. In Proceedings of ECML, 2005.
    • (2005) Proceedings of ECML
    • Kapoor, A.1    Greiner, R.2
  • 13
    • 8644274789 scopus 로고    scopus 로고
    • Feature selection using linear classifier weights: Interaction with classification models
    • D. Mladenic and J. Brank. Feature selection using linear classifier weights: interaction with classification models. In Proceedings of SIGIR, 2004.
    • (2004) Proceedings of SIGIR
    • Mladenic, D.1    Brank, J.2
  • 15
    • 77956201579 scopus 로고    scopus 로고
    • Combined regression and ranking
    • D. Sculley. Combined regression and ranking. In Proceedings of KDD, 2010.
    • (2010) Proceedings of KDD
    • Sculley, D.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.