多重相关性排名模型用于相似物品推荐
Promoted Listings Standard (PLS) helps sellers’ items stand out among billions of listings on eBay. eBay offers several ways to surface PLS listings. One way is placing those items on the search result page at a higher rank, with a “sponsored” badge; another way is recommended by our PLS item recommendation engines on View Item Page. Such PLS items’ high surface rate costs the seller an additional ad rate fee.This helps to increase the likelihood of a sale while staying seller-friendly, as the seller pays only upon sale of the item.
Promoted Listings Standard（PLS）可以帮助卖家的商品在eBay上数十亿个列表中脱颖而出。eBay提供了几种展示PLS列表的方式。一种方式是将这些商品放置在搜索结果页面的更高排名位置，并带有“赞助”标识；另一种方式是通过我们的PLS商品推荐引擎在查看商品页面上推荐。这些PLS商品的高曝光率会给卖家带来额外的广告费用。这有助于增加销售的可能性，同时保持对卖家友好，因为卖家只需在商品销售时支付费用。
This essay focuses on the latter surface way of PLS items, that is the recommendation engines which help users engage with our PLS content, and help us optimally display the items in our uniquely vast and diverse marketplace. One of the recommendations is to recommend similar sponsored items, which is called Promoted Listing SIM (i.e. PLSIM1). The typical user journey for the PLSIM consists of the following steps:
本文重点讨论PLS项目的后期表面方式，即帮助用户与我们的PLS内容互动并帮助我们最佳地展示我们独特广泛和多样化的市场中的物品的推荐引擎。其中一个推荐是推荐类似的赞助物品，称为Promoted Listing SIM（即PLSIM1）。PLSIM的典型用户旅程包括以下步骤：
- The user searches for an item.
- 用户搜索物品。
- Clicks on a result in the search result page, landing on a View Item (VI) page for a listed item, which we refer to as the seed item.
- 在搜索结果页面上点击结果，进入列出物品的查看物品（VI）页面，我们将其称为种子物品。
- Scrolls down the VI page, and sees recommended items in PLSIM.
- 向下滚动VI页面，并在PLSIM中看到推荐的物品。
- Subsequently clicks on an item recommendation and arrives at a new VI page to see the main listing details to either take action (watch, add to cart, buy it now, and more) or check out another, new set of recommended items.
- 随后点击一个商品推荐，进入新的查看商品页面，查看主要的列表详情，可以选择采取行动（关注、加入购物车、立即购买等）或查看另一组新的推荐商品。
In turn, from a machine-learning perspective, our PLSIM engine2 has three stages:
从机器学习的角度来看，我们的PLSIM引擎2有三个阶段：
- It retrieves a subset of can...