Towards a simplified ontology for better e-commerce search

TL;DR

This paper introduces a simplified e-commerce ontology framework for improved search and presents three methods for automatically extracting product classes, enhancing query understanding in semantic search systems.

Contribution

It proposes a tailored, simplified ontology for e-commerce search and compares three automatic extraction methods for product classes.

Findings

The simplified ontology improves search relevance.

Automatic extraction methods vary in performance.

The proposed framework enhances query classification accuracy.

Abstract

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.