Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/117
Title: Identification of suitable websites for digital marketing – an approach using bio-inspired computing
Authors: Kumar, B Suresh
Kar, Arpan Kumar
Igiri, Chinwe
Keywords: Metaheuristics; Henry Garrett Ranking; Cuckoo Search; Analytics; Machine Learning; Internet Applications
Issue Date: Dec-2017
Publisher: International Journal of Engineering & Technology
Citation: Kumar, B. S., Kar, A. K. & Igiri, C.(2017). Identification of suitable websites for digital marketing – an approach using bio-inspired computing. International Journal of Engineering & Technology. DOI: 10.14419/ijet.v7i1.2.9313
Abstract: Due to the immense growth of Internet usage, the point of convergence has moved from physical to the web. The size of the web is increasing at a very fast pace to cater to the fast-evolving needs of businesses, governments, and societies. However, selecting or identifying the best website is challenging. The practical issue to solve the problem comprises two parts. The first part is to identify the assessment criteria for appraising websites. The second is to evaluate the websites in the context of these assessment criteria and screen them to address a specific need. However, this objective is extremely complex and computationally extremely expensive. This research proposes an approach to identifying websites on the Internet. The proposed integrated approach uses the Henry Garrett ranking method and cuckoo search algorithm for ranking and selection of websites for planning digital marketing campaigns.
URI: http://localhost:8080/xmlui/handle/123456789/117
Appears in Collections:Computer Science

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