# Towards a simplified ontology for better e-commerce search

arXiv: https://arxiv.org/abs/1807.02039 · HTML: https://mlsanity.com/paper/1807.02039/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 5 Jul 2018.

## Built on by (most cited first, 1 of 1)

- [Towards Zero-Shot Frame Semantic Parsing with Task Agnostic Ontologies and Simple Labels](https://mlsanity.com/paper/2305.03793/) (2023)

## Abstract (arXiv)

Query Understanding is a semantic search method that can classify tokens in a customer's search query to entities such as Product, Brand, etc. This method can overcome the limitations of bag-of-words methods but requires an ontology. We show that current ontologies are not optimized for search and propose a simplified ontology framework designed specifically for e-commerce search and retrieval. We also present three methods for automatically extracting product classes for the proposed ontology and compare their performance relative to each other.