Designing a Web Spam Classifier Based on Feature Fusion in the Layered Multi-Population Genetic Programming Framework

General information

Authors:
Amir Hosein KEYHANIPOUR, Behzad MOSHIRI

DOI:
10.14201/ADCAIJ2014261527

Volume:
Regular Issue 2 (3), 2013

Keywords:

Web Spam; Feature Fusion; Layered Multi-Population Genetic Programming

Nowadays, Web spam pages are a critical challenge for Web retrieval systems which have drastic influence on the performance of such systems. Although these systems try to combat the impact of spam pages on their final results list, spammers increasingly use more sophisticated techniques to increase the number of views for their intended pages in order to have more commercial success. This paper employs the recently proposed Layered Multi-population Genetic Programming model for Web spam detection task as well application of correlation coefficient analysis for feature space reduction. Based on our tentative results, the designed classifier, which is based on a combination of easy to compute features, has a very reasonable performance in comparison with similar methods.

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