Weiwei Guo, Huiji Gao, Jun Shi, Bo Long, Liang Zhang, Bee-Chung Chen, D. Agarwal
{"title":"搜索和推荐系统的深度自然语言处理","authors":"Weiwei Guo, Huiji Gao, Jun Shi, Bo Long, Liang Zhang, Bee-Chung Chen, D. Agarwal","doi":"10.1145/3292500.3332290","DOIUrl":null,"url":null,"abstract":"Search and recommender systems share many fundamental components including language understanding, retrieval and ranking, and language generation. Building powerful search and recommender systems requires processing natural language effectively and efficiently. Recent rapid growth of deep learning technologies has presented both opportunities and challenges in this area. This tutorial offers an overview of deep learning based natural language processing (NLP) for search and recommender systems from an industry perspective. It first introduces deep learning based NLP technologies, including language understanding and language generation. Then it details how those technologies can be applied to common tasks in search and recommender systems, including query and document understanding, retrieval and ranking, and language generation. Applications in LinkedIn production systems are presented. The tutorial concludes with discussion of future trend.","PeriodicalId":186134,"journal":{"name":"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","volume":"48 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-07-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"17","resultStr":"{\"title\":\"Deep Natural Language Processing for Search and Recommender Systems\",\"authors\":\"Weiwei Guo, Huiji Gao, Jun Shi, Bo Long, Liang Zhang, Bee-Chung Chen, D. Agarwal\",\"doi\":\"10.1145/3292500.3332290\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Search and recommender systems share many fundamental components including language understanding, retrieval and ranking, and language generation. Building powerful search and recommender systems requires processing natural language effectively and efficiently. Recent rapid growth of deep learning technologies has presented both opportunities and challenges in this area. This tutorial offers an overview of deep learning based natural language processing (NLP) for search and recommender systems from an industry perspective. It first introduces deep learning based NLP technologies, including language understanding and language generation. Then it details how those technologies can be applied to common tasks in search and recommender systems, including query and document understanding, retrieval and ranking, and language generation. Applications in LinkedIn production systems are presented. The tutorial concludes with discussion of future trend.\",\"PeriodicalId\":186134,\"journal\":{\"name\":\"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining\",\"volume\":\"48 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-07-25\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"17\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3292500.3332290\",\"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 25th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3292500.3332290","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Deep Natural Language Processing for Search and Recommender Systems
Search and recommender systems share many fundamental components including language understanding, retrieval and ranking, and language generation. Building powerful search and recommender systems requires processing natural language effectively and efficiently. Recent rapid growth of deep learning technologies has presented both opportunities and challenges in this area. This tutorial offers an overview of deep learning based natural language processing (NLP) for search and recommender systems from an industry perspective. It first introduces deep learning based NLP technologies, including language understanding and language generation. Then it details how those technologies can be applied to common tasks in search and recommender systems, including query and document understanding, retrieval and ranking, and language generation. Applications in LinkedIn production systems are presented. The tutorial concludes with discussion of future trend.