Evaluation of Users' Behavior Using Adaptive Fuzzy Prediction Technique

Abstract

User behavior is a considerable determinant of a product’s ecological blow as manufacturing advances authorize enlarged effectiveness of product purpose, the consumer’s alternatives and habits ultimately enclose a major outcome on possessions utilized by the product. A variety of design methods developed in diverse contexts propose chances for engineers and other stakeholders functioning in the ground of sustainable improvement to involve consumers’ actions at communication with the result or system, in result ‘building the user more competent’. Approaches to varying users’ actions from varied amount of fields are evaluated and discussed. But it fails to predict the user behaviors accurately. In this work, Adaptive Fuzzy Prediction technique is presented to interpret and predict the user’s behavior towards product demand, quantity of products, features of the product/services, annual sales with the multi-clustered web usage data. The fuzzy model works on the feedback pattern to arrive at predictive feature of the web usage data value moments, across different time periods, and adapt to the recent consumer behavior and liking of the products and service. Experimentation conduct with real data sets extracted from web log files collected from websites. Performance evaluation is made to show the effectiveness of the proposed technique.