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The Journal of Supercomputing

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16-11-2017

Feature fatigue analysis of product usability using Hybrid ant colony optimization with artificial bee colony approach

Authors: J. Midhunchakkaravarthy, S. SelvaBrunda

Published in: The Journal of Supercomputing | Issue 6/2020

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Abstract

Online users buy a product with more features from e-commerce website. They might be unsatisfied with the some usability issues called feature fatigue. Therefore, it is essential to analyze the product usability. A new method is developed in this work to assist the manufacturers to identify feature that provides the manufacturers for decision-making that to improve the usability of the product to the users. Customer reviews about product usability are gathered from web which is processed by Latent Dirichlet allocation for mining the product feature. The pareto-based genetic algorithm with association rule is used to get an optimal customer’s opinions and product usability. A Hybrid optimization algorithm is proposed for analyzing the feature fatigue on the product usability. The experimental result of the proposed work provides 99% accuracy than existing algorithm.

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Title: Feature fatigue analysis of product usability using Hybrid ant colony optimization with artificial bee colony approach
Authors: J. Midhunchakkaravarthy
S. SelvaBrunda
Publication date: 16-11-2017
Publisher: Springer US
Published in: The Journal of Supercomputing / Issue 6/2020
Print ISSN: 0920-8542
Electronic ISSN: 1573-0484
DOI: https://doi.org/10.1007/s11227-017-2178-4

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