{"id":12844,"date":"2023-01-04T13:13:21","date_gmt":"2023-01-04T18:13:21","guid":{"rendered":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/?p=12844"},"modified":"2023-01-04T13:13:21","modified_gmt":"2023-01-04T18:13:21","slug":"how-pinterest-leverages-realtime-user-actions-in-recommendation-to-boost-homefeed-engagement-volume","status":"publish","type":"post","link":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/how-pinterest-leverages-realtime-user-actions-in-recommendation-to-boost-homefeed-engagement-volume\/12844\/","title":{"rendered":"How Pinterest Leverages Realtime User Actions in Recommendation to Boost Homefeed Engagement Volume"},"content":{"rendered":"Originally published in Pinterest Engineering Blog, Nov 4, 2022.\u00a0 In this blog post, we will demonstrate how we improved Pinterest Homefeed engagement volume from a machine learning model design perspective \u2014 by leveraging realtime user action features in Homefeed recommender system. Background The Homepage of Pinterest is the one of most important surfaces for pinners to discover inspirational ideas and contributes to a large fraction of overall user engagement. The pins shown in the top positions on the Homefeed need to be personalized to create an engaging pinner experience. We retrieve a small fraction of the large volume <a href=\"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/how-pinterest-leverages-realtime-user-actions-in-recommendation-to-boost-homefeed-engagement-volume\/12844\/\" class=\"more-link\">(more&hellip;)<\/a>","protected":false},"excerpt":{"rendered":"<p>Originally published in Pinterest Engineering Blog, Nov 4, 2022.\u00a0 In this blog post, we will demonstrate how we improved Pinterest Homefeed engagement volume from a machine learning model design perspective \u2014 by leveraging realtime user action features in Homefeed recommender system. Background The Homepage of Pinterest is the one of most important surfaces for pinners [&hellip;]<\/p>\n","protected":false},"author":72,"featured_media":0,"comment_status":"open","ping_status":"open","sticky":false,"template":"","format":"standard","meta":{"footnotes":"","_links_to":"","_links_to_target":""},"categories":[11,48],"tags":[879,368,791,243,8],"class_list":["post-12844","post","type-post","status-publish","format-standard","hentry","category-industry-news","category-left-hand","tag-ai","tag-artificial-intelligence","tag-deep-learning","tag-machine-learning","tag-predictive-analytics"],"_links":{"self":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/12844","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/users\/72"}],"replies":[{"embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/comments?post=12844"}],"version-history":[{"count":1,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/12844\/revisions"}],"predecessor-version":[{"id":12845,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/posts\/12844\/revisions\/12845"}],"wp:attachment":[{"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/media?parent=12844"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/categories?post=12844"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.predictiveanalyticsworld.com\/machinelearningtimes\/wp-json\/wp\/v2\/tags?post=12844"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}