Open AccessIdentification of suitable websites for digital marketing – an approach using bio-inspired computing
Author(s) -
B. Suresh Kumar,
Deepshikha Bharghava,
Arpan Kumar Kar,
Chinwe Peace Igiri
Publication year - 2017
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.2.9313
Subject(s) - ranking (information retrieval) , computer science , pace , the internet , identification (biology) , context (archaeology) , cuckoo search , point (geometry) , digital marketing , world wide web , data science , selection (genetic algorithm) , convergence (economics) , online advertising , search engine optimization , information retrieval , machine learning , paleontology , botany , geometry , mathematics , geodesy , particle swarm optimization , biology , geography , economic growth , economics
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 the 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. 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 identify websites from 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.