Report
How to Grow a (Product) Tree: Personalized Category Suggestions for eCommerce Type-Ahead
| العنوان: | How to Grow a (Product) Tree: Personalized Category Suggestions for eCommerce Type-Ahead |
|---|---|
| المؤلفون: | Tagliabue, Jacopo, Yu, Bingqing, Beaulieu, Marie |
| سنة النشر: | 2020 |
| المجموعة: | Computer Science Statistics |
| مصطلحات موضوعية: | Computer Science - Machine Learning, Computer Science - Information Retrieval, Statistics - Machine Learning |
| الوصف: | In an attempt to balance precision and recall in the search page, leading digital shops have been effectively nudging users into select category facets as early as in the type-ahead suggestions. In this work, we present SessionPath, a novel neural network model that improves facet suggestions on two counts: first, the model is able to leverage session embeddings to provide scalable personalization; second, SessionPath predicts facets by explicitly producing a probability distribution at each node in the taxonomy path. We benchmark SessionPath on two partnering shops against count-based and neural models, and show how business requirements and model behavior can be combined in a principled way. |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2005.12781 |
| رقم الانضمام: | edsarx.2005.12781 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |