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This paper takes customer preference sequence data and proposes a relationship model between customer preference orientation and customer characteristics which use the characteristics of the supply chain to draw on symbolic sequence clustering. It focuses on the study of symbol sequence data properties, and analyzes the essence of preference symbol sequence clustering based on symbolic sequencing in both formalized and materialized ways. It studies the application of the self-organizing feature map as a symbol sequence clustering algorithm, and makes the comparison between clustering models so that the research approach to study the structure of market segments based on consumer preferences can be realized in practice.
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