@inproceedings{tagliabue-etal-2020-grow,
title = "How to Grow a (Product) Tree: Personalized Category Suggestions for e{C}ommerce Type-Ahead",
author = "Tagliabue, Jacopo and
Yu, Bingqing and
Beaulieu, Marie",
editor = "Malmasi, Shervin and
Kallumadi, Surya and
Ueffing, Nicola and
Rokhlenko, Oleg and
Agichtein, Eugene and
Guy, Ido",
booktitle = "Proceedings of the 3rd Workshop on e-Commerce and NLP",
month = jul,
year = "2020",
address = "Seattle, WA, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.ecnlp-1.2",
doi = "10.18653/v1/2020.ecnlp-1.2",
pages = "7--18",
abstract = "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.",
}
Markdown (Informal)
[How to Grow a (Product) Tree: Personalized Category Suggestions for eCommerce Type-Ahead](https://aclanthology.org/2020.ecnlp-1.2) (Tagliabue et al., ECNLP 2020)
ACL