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A Human Behavior Analyzer Framework for consumer product search engines

In today consumer world, product search engines have been played key roles for consumer information seeking and decision making process. However, due to the volume, variety and velocity of information plus the nature of human beings, it becomes very hard to identify what information and how it is used by a consumer. Therefore, in this paper a Human Behavior Analyzer Framework is proposed to gain some relevant insight information for consumers. In doing so, a stochastic approach based on Markov Chain concepts has been employed and some experimental results are presented to confirm the effectiveness of proposed method.