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Volumn , Issue , 2011, Pages 155-163

Text mining techniques for leveraging positively labeled data

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; MACHINE LEARNING; NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 85121209205     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper
Times cited : (13)

References (16)
  • 1
    • 27244440347 scopus 로고    scopus 로고
    • Applying Support Vector Machines to Imballanced Datasets
    • Abkani, R., S. Kwek, et al. (2004). Applying Support Vector Machines to Imballanced Datasets. ECML.
    • (2004) ECML
    • Abkani, R.1    Kwek, S.2
  • 5
    • 33746218517 scopus 로고    scopus 로고
    • Efficient optimization of support vector machine learning parameters for unbalanced datasets
    • Eitrich, T. and B. Lang (2005). "Efficient optimization of support vector machine learning parameters for unbalanced datasets." Journal of Computational and Applied Mathematics 196(2): 425-436.
    • (2005) Journal of Computational and Applied Mathematics , vol.196 , Issue.2 , pp. 425-436
    • Eitrich, T.1    Lang, B.2
  • 7
    • 84876811202 scopus 로고    scopus 로고
    • RCV1: A New Benchmark Collection for Text Categorization Research
    • Lewis, D. D., Y. Yang, et al. (2004). "RCV1: A New Benchmark Collection for Text Categorization Research." Journal of Machine Learning Research 5: 361-397.
    • (2004) Journal of Machine Learning Research , vol.5 , pp. 361-397
    • Lewis, D. D.1    Yang, Y.2
  • 8
    • 33845772427 scopus 로고    scopus 로고
    • Learning when data sets are imbalanced and when costs are unequal and unknown
    • Maloof, M. A. (2003). Learning when data sets are imbalanced and when costs are unequal and unknown. ICML 2003, Workshop on Imballanced Data Sets.
    • (2003) ICML 2003, Workshop on Imballanced Data Sets
    • Maloof, M. A.1
  • 10
    • 0003309997 scopus 로고    scopus 로고
    • Text Classification from Labeled and Unlabeled Documents using EM
    • Nigam, K., A. K. McCallum, et al. (1999). "Text Classification from Labeled and Unlabeled Documents using EM." Machine Learning: 1-34.
    • (1999) Machine Learning , pp. 1-34
    • Nigam, K.1    McCallum, A. K.2
  • 12
    • 5044241106 scopus 로고    scopus 로고
    • MedPost: A part of speech tagger for biomedical text
    • Smith, L., T. Rindflesch, et al. (2004). "MedPost: A part of speech tagger for biomedical text." Bioinformatics 20: 2320-2321.
    • (2004) Bioinformatics , vol.20 , pp. 2320-2321
    • Smith, L.1    Rindflesch, T.2
  • 13
    • 0042868698 scopus 로고    scopus 로고
    • Support vector machine active learning with applications to text classification
    • Tong, S. and D. Koller (2001). "Support vector machine active learning with applications to text classification." Journal of Machine Learning Research 2: 45-66.
    • (2001) Journal of Machine Learning Research , vol.2 , pp. 45-66
    • Tong, S.1    Koller, D.2
  • 14
    • 61449170039 scopus 로고    scopus 로고
    • Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?
    • Weiss, G., K. McCarthy, et al. (2007). Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs? Proceedings of the 2007 International Conference on Data Mining.
    • (2007) Proceedings of the 2007 International Conference on Data Mining
    • Weiss, G.1    McCarthy, K.2
  • 15
    • 14344259207 scopus 로고    scopus 로고
    • Solving large scale linear prediction problems using stochastic gradient descent algorithms
    • Omnipress
    • Zhang, T. (2004). Solving large scale linear prediction problems using stochastic gradient descent algorithms. Twenty-first International Conference on Machine learning, Omnipress.
    • (2004) Twenty-first International Conference on Machine learning
    • Zhang, T.1


* 이 정보는 Elsevier사의 SCOPUS DB에서 KISTI가 분석하여 추출한 것입니다.