Uber配送搜索平台的演变与规模
Search is a primary discovery funnel for Uber Eats: a large share of orders start with people typing into the search bar to find stores, dishes, and grocery items. Strong search directly translates into higher conversion, better basket quality, and faster time-to-order—especially for long-tail queries, new or seasonal items, and multilingual markets. When search misses intent, people bounce or fall back to browsing. When it understands intent, they find what they want in seconds.
搜索是Uber Eats的主要发现渠道：大量订单始于人们在搜索栏中输入以查找商店、菜肴和杂货。强大的搜索直接转化为更高的转化率、更好的购物车质量和更快的下单时间——尤其是对于长尾查询、新品或季节性商品以及多语言市场。当搜索未能捕捉意图时，人们会跳出或回到浏览。当它理解意图时，他们能在几秒钟内找到所需的内容。
Traditional search stacks begin with lexical matching, which is fast and effective when queries exactly match document text. But real queries are challenging—synonyms (“soda” versus “soft drink”), typos (“mozzarela”), shorthand (“gf pizza”), language mix (“pan” meaning bread in Spanish, but a container for cooking in English), and context (“apple” the fruit vs the company). Lexical methods see strings, not meaning, and aren’t suitable for such queries, producing bad search results.
传统的搜索堆栈始于词汇匹配，当查询与文档文本完全匹配时，这种方法快速有效。但真实的查询是具有挑战性的——同义词（“soda”与“soft drink”）、拼写错误（“mozzarela”）、简写（“gf pizza”）、语言混合（“pan”在西班牙语中意为面包，但在英语中是烹饪容器）和上下文（“apple”作为水果与公司）。词汇方法只看到字符串，而不是意义，因此不适合此类查询，产生糟糕的搜索结果。
Semantic search shifts from matching words to matching meaning. It encodes queries and documents into vectors in the same space, so semantically similar things are close—even without keyword overlap. When properly used, it delivers a search experience that better captures someone’s intent across verticals (stores, dishes, items) and languages.
语义搜索从匹配单词转向匹配意义。它将查询和文档编码为同一空间中的向量，因此语义上相似的事物是接近的——即使没有关键词重叠。当正确使用时，它提供了一种更好地捕捉用户意图的搜索体验，适用于各个垂直领域（商店、菜肴、商品）和语言。
Establishing semantic search at scale for industry applications is more than training a model, but instead a whole tech stack including model deployment, ANN (Approximate Nearest Neighbor) index serving at scale, monitoring, version control, and so on. This bl...