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IJIT
2004

Combining ILP with Semi-supervised Learning for Web Page Categorization

9 years 2 months ago
Combining ILP with Semi-supervised Learning for Web Page Categorization
This paper presents a semi-supervised learning algorithm called Iterative-Cross Training (ICT) to solve the Web pages classification problems. We apply Inductive logic programming (ILP) as a strong learner in ICT. The objective of this research is to evaluate the potential of the strong learner in order to boost the performance of the weak learner of ICT. We compare the result with the supervised Naive Bayes, which is the well-known algorithm for the text classification problem. The performance of our learning algorithm is also compare with other semi-supervised learning algorithms which are Co-Training and EM. The experimental results show that ICT algorithm outperforms those algorithms and the performance of the weak learner can be enhanced by ILP system. Keywords--Inductive Logic Programming, Semi-supervised Learning, Web Page Categorization.
Nuanwan Soonthornphisaj, Boonserm Kijsirikul
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2004
Where IJIT
Authors Nuanwan Soonthornphisaj, Boonserm Kijsirikul
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