تصنيف البند هو تطبيق مهم لتصنيف النص في التجارة الإلكترونية بسبب تأثيرها على تجربة التسوق عبر الإنترنت للمستخدمين.يتم استخدام فئة واحدة من تقنيات تصنيف النص التي اكتسبت الاهتمام مؤخرا المعلومات الدلالية للملصقات لتوجيه مهمة التصنيف.لقد أجرينا تحقيقا منهجيا في الفوائد المحتملة لهذه الطرق على بيانات حقيقية مجموعة من شركة تجارة إلكترونية كبرى في اليابان.علاوة على ذلك، باستخدام مساحة مفرط لتضمين ملصقات المنتجات التي يتم تنظيمها في هيكل هرمي أدت إلى أداء أفضل مقارنة باستخدام تضمين الفضاء الإقليدي التقليدي.توضح هذه النتائج كيف يمكن للتعلم الموجه على التسمية تحسين أنظمة تصنيف البند في مجال التجارة الإلكترونية.
Item categorization is an important application of text classification in e-commerce due to its impact on the online shopping experience of users. One class of text classification techniques that has gained attention recently is using the semantic information of the labels to guide the classification task. We have conducted a systematic investigation of the potential benefits of these methods on a real data set from a major e-commerce company in Japan. Furthermore, using a hyperbolic space to embed product labels that are organized in a hierarchical structure led to better performance compared to using a conventional Euclidean space embedding. These findings demonstrate how label-guided learning can improve item categorization systems in the e-commerce domain.
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