Automated Blog Design System with a Population-Based Artificial Immune Algorithm

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Abstract

Advances in the Web have eventually arrived at the new concept of ’Web 2.0’ and the Blog is a representing service of Web 2.0. Despite the dramatic increase of the Blog users and distinctive characteristics of them, the classical processes of blog creation have difficulties in taking user’s preference into account without knowledge about Web programming. Thus, we developed an automated blog design generation system through a population-based artificial immune algorithm. In the algorithm, a user’s requirements and a blog design correspond to, respectively, an antigen and an antibody of vertebrate immune system. A slicing tree layout and the HSV color space model are used to represent a blog design as a string format of an antibody. Design quality quantification rules of a blog design and a distance measure between two different blog designs are devised to compose an affinity function. The system shows ability to provide new blogs to the user quickly and easily considering user’s preferences with good algorithmic performance when it compared with conventional genetic algorithms.

This work was supported by Korea Ministry of Information and Communication under Grant C109006020001. KH and JL were partly supported by the IT R&D program of MIC/IITA [2005-S069-02]. We would like to thank CHUNG Moon Soul Center for BioInformation and BioElectronics for providing research facilities.