Shopify 如何通过实时机器学习改进消费者搜索意图

In the dynamic landscape of commerce, Shopify merchants rely on our platform's ability to seamlessly and reliably deliver highly relevant products to potential customers. Therefore, a rich and intuitive search experience is an essential part of our offering. Over the past year, Shopify has been integrating AI-powered search capabilities into our merchants’ storefronts. Shopify Storefront Search has transformed the way consumers can shop online. With Semantic Search, we went beyond keyword matching. We improved our understanding of the intent behind a consumer’s search, so that we could match a search with the most relevant products.

在充满活力的商业环境中，Shopify 商家依赖我们平台的能力，能够无缝且可靠地将高度相关的产品传递给潜在客户。因此，丰富且直观的搜索体验是我们产品的重要组成部分。在过去的一年里，Shopify 一直在将AI 驱动的搜索功能集成到我们的商家店面中。Shopify Storefront Search 改变了消费者在线购物的方式。通过语义搜索，我们超越了关键词匹配。我们改进了对消费者搜索意图的理解，从而能够将搜索与最相关的产品匹配。

The net result is helping our merchants boost their sales while offering positive interactive experiences for their consumers. It’s a win-win!

最终结果是帮助我们的商家提升销售额，同时为他们的消费者提供积极的互动体验。这是双赢的局面！

Building ML assets with real-time Embeddings

使用实时嵌入构建ML资产

Around the same time, Shopify also started investing in creating foundational machine learning (ML) assets. These assets are built as a shared repository of ML primitives which are used as reusable building blocks for more sophisticated AI systems. Shopify Storefront Search is the perfect use case for these ML assets. Complex systems like this need primitives that can transform both text and images into data formats it can process.

大约在同一时间，Shopify也开始投资创建基础的机器学习（ML）资产。这些资产被构建为ML原语的共享库，用作更复杂AI系统的可重用构建块。Shopify Storefront Search是这些ML资产的完美用例。像这样的复杂系统需要能够将文本和图像转换为它可以处理的数据格式的原语。

How do we do that?

我们如何做到这一点？

Enter embeddings, which translate textual and visual content into numerical vectors in a high-dimensional space. This transformation allows us to measure the similarity between different pieces of content, whether text or images, enabling more accurate and context-aware search results.

引入嵌入，它将文本和视觉内容转换为高维空间中的数值向量。这种转换使我们能够测量不同内容之间的相似...