A Glowworm Optimization Method for the Design of Web Services

A Glowworm Optimization Method for the Design of Web Services

Автор: Koffka Khan, Ashok Sahai

Журнал: International Journal of Intelligent Systems and Applications(IJISA) @ijisa

Статья в выпуске: 10 vol.4, 2012 года.

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A method for adaptive usability evaluation of B2C eCommerce web services is proposed. For measuring eCommerce usability a checklist integrating eCommerce quality and usability is developed. By a Glowworm swarm optimization (GSO) neural networks-based model the usability dimensions and their checklist items are adaptively selected. A case study for usability evaluation of an eCommerce anthurium retail website is carried out. The experimental results show that GSO with neural networks supports the allocation of usability problems and the defining of relevant improvement measures. The main advantage of the approach is the adaptive selection of most significant checklist dimensions and items and thus significant reduction of the time for usability evaluation and design.

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ECommerce, Usability, Glowworm swarm optimization, Neural Networks

Короткий адрес: https://sciup.org/15010322

IDR: 15010322

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