A Glowworm Optimization Method for the Design of Web Services

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Koffka Khan 1,* Ashok Sahai 2

1. Department of Computing and Information Technology, The University of the West Indies, St. Augustine Campus @ TRINIDAD

2. Department of Mathematics and Statistics, The University of the West Indies, St. Augustine Campus @ TRINIDAD

* Corresponding author.

DOI: https://doi.org/10.5815/ijisa.2012.10.10

Received: 17 Jan. 2012 / Revised: 3 May 2012 / Accepted: 11 Jul. 2012 / Published: 8 Sep. 2012

Index Terms

eCommerce, Usability, Glowworm swarm optimization, Neural Networks


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.

Cite This Paper

Koffka Khan, Ashok Sahai, "A Glowworm Optimization Method for the Design of Web Services", International Journal of Intelligent Systems and Applications(IJISA), vol.4, no.10, pp.89-102, 2012. DOI:10.5815/ijisa.2012.10.10


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