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Title: A self-Adaptive customer-oriented framework for intelligent strategic marketing: A multi-Agent system approach to website development for learning institutions
Authors: Mahmoud, M.A. 
Ahmad, M.S. 
Keywords: Artificial intelligence
Association rules
Multi-agent systems
Issue Date: 2016
Abstract: In this paper, we argue that current universities' websites provide essential information for visitors but they do not support strategic marketing issues. Consequently, this paper discusses the possibility of proposing an intelligent strategic marketing via self-Adaptive customer-oriented website. The idea is to provide a satisfying factor for visitors once they click and open a university's website page. The proposed framework consists of three main phases which are, e-questionnaire development, grouping society process, and tactical adaptation process. The first phase is achieved by conducting interviews with different people from different areas about their main concerns when they select a university and subsequently come up with an e-questionnaire. The second phase is operated by a multi-Agent system that analyzes a society member's responses to the e-questionnaire and discovers the member's various preferences. The third phase is operated by a facilitator agent that performs tactical adaption to the website's content via a customer-oriented approach. The customer-oriented approach works on matching each group preferences with the website content. Finally, the self-Adaptive website displays materials to these groups according to their preferences. © 2015 IEEE.
DOI: 10.1109/ISAMSR.2015.7379121
Appears in Collections:CSIT Scholarly Publication

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