Abstract
It is important for the strategy of product sales to investigate the customer’s sensibility and preference degree in the environment that the process of material development has been changed focusing on the customer center. In this paper we identify collaborative filtering and content-based filtering as independent technologies for information filtering. We propose the Fashion Design Recommender Agent System of textile design applying two-way combined filtering technologies as one of methods in the material development centered on customer’s representative sensibility and preference. We build the database founded on the sensibility adjective to develop textile design by extracting the representative sensibility adjective form user’s sensibility and preference about textiles. Our system recommends textile designs to a customer who has a similar propensity about textile. Ultimately, this paper suggests empirical applications to verify the adequacy and the validity on this system.
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Jung, KY., Na, YJ., Lee, JH. (2003). FDRAS: Fashion Design Recommender Agent System Using the Extraction of Representative Sensibility and the Two-Way Combined Filtering on Textile. In: Mařík, V., Retschitzegger, W., Štěpánková, O. (eds) Database and Expert Systems Applications. DEXA 2003. Lecture Notes in Computer Science, vol 2736. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-45227-0_62
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DOI: https://doi.org/10.1007/978-3-540-45227-0_62
Publisher Name: Springer, Berlin, Heidelberg
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