{"title":"基于语义关系的文档搜索和排序","authors":"Boanerges Aleman-Meza","doi":"10.1109/ICDEW.2006.131","DOIUrl":null,"url":null,"abstract":"Just as the link structure of the web is a critical component in today's web search, complex relationships (i.e., the different ways the dots are connected) will be an important component in tomorrow's web search technologies. In this paper, I summarize my research on answering the question of: How we can exploit semantic relationships of named-entities to improve relevance in search and ranking of documents? The intuition of my approach is to first analyze the relationships of namedentities with respect to a query. Second, relevance weights, which are assigned by human experts, can then be used to guarantee results within a relevance threshold. These relevance measures can be applied both for searching and ranking of documents.","PeriodicalId":331953,"journal":{"name":"22nd International Conference on Data Engineering Workshops (ICDEW'06)","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2006-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Searching and Ranking Documents based on Semantic Relationships\",\"authors\":\"Boanerges Aleman-Meza\",\"doi\":\"10.1109/ICDEW.2006.131\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Just as the link structure of the web is a critical component in today's web search, complex relationships (i.e., the different ways the dots are connected) will be an important component in tomorrow's web search technologies. In this paper, I summarize my research on answering the question of: How we can exploit semantic relationships of named-entities to improve relevance in search and ranking of documents? The intuition of my approach is to first analyze the relationships of namedentities with respect to a query. Second, relevance weights, which are assigned by human experts, can then be used to guarantee results within a relevance threshold. These relevance measures can be applied both for searching and ranking of documents.\",\"PeriodicalId\":331953,\"journal\":{\"name\":\"22nd International Conference on Data Engineering Workshops (ICDEW'06)\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2006-04-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"22nd International Conference on Data Engineering Workshops (ICDEW'06)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDEW.2006.131\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"22nd International Conference on Data Engineering Workshops (ICDEW'06)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDEW.2006.131","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Searching and Ranking Documents based on Semantic Relationships
Just as the link structure of the web is a critical component in today's web search, complex relationships (i.e., the different ways the dots are connected) will be an important component in tomorrow's web search technologies. In this paper, I summarize my research on answering the question of: How we can exploit semantic relationships of named-entities to improve relevance in search and ranking of documents? The intuition of my approach is to first analyze the relationships of namedentities with respect to a query. Second, relevance weights, which are assigned by human experts, can then be used to guarantee results within a relevance threshold. These relevance measures can be applied both for searching and ranking of documents.