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دسته بندی:
تجارت الکترونیک - electronic commerce
سال انتشار:
2018
عنوان انگلیسی مقاله:
Recommendation system development for fashion retail e-commerce
ترجمه فارسی عنوان مقاله:
تحقیق روی سیستم توصیه برای تجارت الکترونیک خرده فروشی مسایل مد
منبع:
Electronic Commerce Research and Applications Volume 28, March–April 2018, Pages 94-101
نویسنده:
Hyunwoo Hwangbo, Yang Sok Kim, Kyung Jin Cha
چکیده انگلیسی:
This study presents a real-world collaborative filtering recommendation system implemented in a large Korean fashion company that sells fashion products through both online and offline shopping malls. The company’s recommendation environment displays the following unique characteristics: First, the company’s online and offline stores sell the same products. Second, fashion products are usually seasonal, so customers’ general preference changes according to the time of year. Last, customers usually purchase items to replace previously preferred items or purchase items to complement those already bought. We propose a new system called K-RecSys, which extends the typical item-based collaborative filtering algorithm by reflecting the above domain characteristics. K-RecSys combines online product click data and offline product sale data weighted to reflect the online and offline preferences of customers. It also adopts a preference decay function to reflect changes in preferences over time, and finally recommends substitute and complementary products using product category information. We conducted an A/B test in the actual operating environment to compare K-RecSys with the existing collaborative filtering system implemented with only online data. Our experimental results show that the proposed system is superior in terms of product clicks and sales in the online shopping mall and its substitute recommendations are adopted more frequently than complementary recommendations.
keywords: Collaborative filtering |E-commerce |Fashion industry |Recommendation system
قیمت: رایگان
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