{"title":"重影:大规模零售搜索中上下文化的内联查询完成","authors":"Lakshmi Ramachandran, Uma Murthy","doi":"10.1145/3298689.3346995","DOIUrl":null,"url":null,"abstract":"Query auto-completion presents a ranked list of queries as suggestions for a user-entered prefix. Ghosting is the process of auto-completing a search recommendation by highlighting the suggested text inline within the search box. We propose the use of a behavior-based recommendation model along with customer search context to ghost on high-confidence queries. We tested ghosting on a retail production system, on over 140 million search sessions. We found that session-context based ghosting significantly increased the acceptance of offered suggestions by 6.18%, reduced misspellings among searches by 4.42%, and improved net sales by 0.14%.","PeriodicalId":215384,"journal":{"name":"Proceedings of the 13th ACM Conference on Recommender Systems","volume":"17 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Ghosting: contextualized inline query completion in large scale retail search\",\"authors\":\"Lakshmi Ramachandran, Uma Murthy\",\"doi\":\"10.1145/3298689.3346995\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Query auto-completion presents a ranked list of queries as suggestions for a user-entered prefix. Ghosting is the process of auto-completing a search recommendation by highlighting the suggested text inline within the search box. We propose the use of a behavior-based recommendation model along with customer search context to ghost on high-confidence queries. We tested ghosting on a retail production system, on over 140 million search sessions. We found that session-context based ghosting significantly increased the acceptance of offered suggestions by 6.18%, reduced misspellings among searches by 4.42%, and improved net sales by 0.14%.\",\"PeriodicalId\":215384,\"journal\":{\"name\":\"Proceedings of the 13th ACM Conference on Recommender Systems\",\"volume\":\"17 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-09-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 13th ACM Conference on Recommender Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3298689.3346995\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 13th ACM Conference on Recommender Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3298689.3346995","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Ghosting: contextualized inline query completion in large scale retail search
Query auto-completion presents a ranked list of queries as suggestions for a user-entered prefix. Ghosting is the process of auto-completing a search recommendation by highlighting the suggested text inline within the search box. We propose the use of a behavior-based recommendation model along with customer search context to ghost on high-confidence queries. We tested ghosting on a retail production system, on over 140 million search sessions. We found that session-context based ghosting significantly increased the acceptance of offered suggestions by 6.18%, reduced misspellings among searches by 4.42%, and improved net sales by 0.14%.