{"title":"从网络搜索相关性到垂直搜索相关性","authors":"Yi Chang","doi":"10.1145/2766462.2776787","DOIUrl":null,"url":null,"abstract":"Web search relevance is a billion dollar challenge, while there is a disadvantage of backwardness in web search competition. Vertical search result can be incorporated to enrich web search content, therefore vertical search relevance is critical to provide differentiated search results. Machine learning based ranking algorithms have shown their effectiveness for both web search and vertical search tasks. In this talk, the speaker will not only introduce state-of-the-art ranking algorithms for web search, but also cover the challenges to improve relevance of various vertical search engines: local search, shopping search, news search, etc.","PeriodicalId":297035,"journal":{"name":"Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-08-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"From Web Search Relevance to Vertical Search Relevance\",\"authors\":\"Yi Chang\",\"doi\":\"10.1145/2766462.2776787\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Web search relevance is a billion dollar challenge, while there is a disadvantage of backwardness in web search competition. Vertical search result can be incorporated to enrich web search content, therefore vertical search relevance is critical to provide differentiated search results. Machine learning based ranking algorithms have shown their effectiveness for both web search and vertical search tasks. In this talk, the speaker will not only introduce state-of-the-art ranking algorithms for web search, but also cover the challenges to improve relevance of various vertical search engines: local search, shopping search, news search, etc.\",\"PeriodicalId\":297035,\"journal\":{\"name\":\"Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-08-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 38th International ACM SIGIR Conference on Research and Development in Information Retrieval\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/2766462.2776787\",\"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 38th International ACM SIGIR Conference on Research and Development in Information Retrieval","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/2766462.2776787","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
From Web Search Relevance to Vertical Search Relevance
Web search relevance is a billion dollar challenge, while there is a disadvantage of backwardness in web search competition. Vertical search result can be incorporated to enrich web search content, therefore vertical search relevance is critical to provide differentiated search results. Machine learning based ranking algorithms have shown their effectiveness for both web search and vertical search tasks. In this talk, the speaker will not only introduce state-of-the-art ranking algorithms for web search, but also cover the challenges to improve relevance of various vertical search engines: local search, shopping search, news search, etc.