Modeling the Structure of Recommending Interfaces with Adjustable Influence on Users

Recommending interfaces are usually integrated with marketing processes and are targeted to increasing sales with the use of persuasion and influence methods to motivate users to follow recommendations. In this paper is presented an approach based on decomposition of recommending interface into elements with adjustable influence levels. A fuzzy inference model is proposed to represent the system characteristics with the ability to adjust the parameters of the interface to acquire results and increase customer satisfaction.

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