IRJul 5, 2018

Towards a simplified ontology for better e-commerce search

arXiv:1807.02039v17 citations
Originality Incremental advance
AI Analysis

This work targets e-commerce platforms to improve search accuracy, but it is incremental as it builds on existing query understanding methods.

The paper addresses the problem of suboptimal ontologies in e-commerce search by proposing a simplified ontology framework specifically designed for this domain, and presents three automated methods for extracting product classes, with performance comparisons provided.

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.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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