Abstract
It is important to understand consumer needs correctly and clarify target of goods and service in marketing. In recent years, as information processing technology develops, video image analysis also has become as important tool for customer behavior analysis. It is said that discovering consumers’ purchase patterns of choosing purchased goods may be possible by using video data. Video is sequential temporal data, so time-series data mining technique is necessary. And generally consumer behavior is ambiguous. To respond to these situation, we are now developing a collective intelligence-based sequential pattern mining approach with high robustness and adaptability, and this time, we have succeeded in visualizing the relation of goods that they are continuously touched up by consumer.
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Tsuboi, K., Shinoda, K., Suwa, H., Kurihara, S. (2015). Collective Intelligence-Based Sequential Pattern Mining Approach for Marketing Data. In: Aiello, L., McFarland, D. (eds) Social Informatics. SocInfo 2014. Lecture Notes in Computer Science(), vol 8852. Springer, Cham. https://doi.org/10.1007/978-3-319-15168-7_44
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DOI: https://doi.org/10.1007/978-3-319-15168-7_44
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