I am proud to share the slides for “Semantic Equivalence of e-Commerce Queries”, which my eBay colleague Aritra Mandal presented this morning at the KDD 2023 Workshop on E-Commerce and Natural Language Processing (ECNLP). Our work demonstrates how to measure e-Commerce query similarity by aggregating historical searcher behavior for frequent queries and then training a sentence transformer model that generalizes to unseen queries. We show results for proprietary eBay data as well as for the Amazon Shopping Queries Dataset used in last year’s KDD Cup.

Search application developers put a lot of effort into optimizing the ranking of search results, especially in areas like ecommerce, where incremental ranking improvements translate directly to revenue. As a result, there have been decades of investment into methods that apply machine learning to ranking, and, more recently, into neural…

There’s a lot of writing about search — especially about ranking and relevance. And recently there’s been an increased focus on the particular challenges of query understanding. But, surprisingly, there hasn’t been much discussion of content understanding. This post will be the first of many to address this gap. Content understanding is the foundation of the search process. Let’s…

This publication is a series of posts devoted to query understanding. Each post is self-contained, but there is a natural progression. If you’d like to read them all, start with the first one.

As a search specialist, my main goal is to improve searcher happiness. Sure, companies pay me to improve business metrics like conversion rate and revenue, but I mostly accomplish this by helping searchers find what they are looking for, and, in the case of ecommerce, buy it. But what is…

We have reached the stage of generative AI where artists, authors, and performers are convinced that AI is stealing their lives — and, perhaps more importantly, their livelihoods. This dystopian theme is showing up in lawsuits, strikes, and, of course, Black Mirror episodes. Yet, as far as I can tell…

Search result snippets, also known as query-biased summaries, are the additional context included with each result on the search results page. They are an essential tool to help searchers find what they’re looking for. Snippets serve more than one purpose. The primary purpose of snippets is to communicate to the searcher how a result is relevant…

Let me start with the disclaimer that this post describes an embryonic idea, not an approach that I have validated through analysis or experimentation. With that out of the way, let us get into it! Query Similarity As long-time readers know, I have a keen interest in query understanding, and especially in…

When my colleagues and I at Endeca started working on faceted search in 1999, our model of the search journey was that most searchers start with broadly expressed information needs, and then progressively narrow down those needs by specifying facet values as refinements. For example, a searcher might start with…