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Multiple Instance Learning with Multiple Objective Genetic Programming for Web Mining

delete2011-01-01
delete15
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A
Amelia Zafra *
E
Eva Gibaja
S
Sebastián Ventura
DOI:10.1016/j.asoc.2009.10.021delete
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Abstract

Abstract

En 中文
This paper introduces a multi-objective grammar based genetic programming algorithm, MOG3P-MI, to solve a Web Mining problem from the perspective of multiple instance learning. This algorithm is evaluated and compared to other algorithms that were previously used to solve this problem. Computational experiments show that the MOG3P-MI algorithm obtains the best results, adds comprehensibility and clarity to the knowledge discovery process and overcomes the main drawbacks of previous techniques obtaining solutions which maintain a balance between conflicting measurements like sensitivity and specificity. (c) 2009 Elsevier B.V. All rights reserved.
Keywords:
Multi-instance learning
Multi-objective learning
Genetic programming
Web Mining
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Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.

Journal

Applied Soft Computing cover
Applied Soft Computing
IF:
6.6
Papers:
1.4W
Citations:
4.8W

Organization

U
universidad de cordoba
Scholars:
1.0W
Papers: 8.4K
Citations: 6