A Big Data application framework for consumer behavior analysis

More than ever before, the amount of data about consumers, suppliers and products has been exploding in today consumer world referred as “Big Data”. In addition, more data is available to the consumer world from multiple sources including social network platforms. In order to deal with such amount of data, a new emerging technology “Big Data Analytics” is explored and employed for analyzing consumer behaviors and searching their information needs. Specifically, this paper proposes a Big Data application framework for analyzing consumer behaviors by using topological data structure, co-occurrence methodology and Markov chain theory. First, the consumer related data is translated into a topological data structure. Second, using topological relationships, a co-occurrence matrix is formed to deduce Markov chain model for consumer behavior analysis. Finally, some simulation results are shown to confirm the effectiveness of the proposed framework.