{"title":"图形文档的索引方法","authors":"S. Tabbone, Daniel Zuwala","doi":"10.1109/ICDAR.2007.55","DOIUrl":null,"url":null,"abstract":"In this paper, a method to browse symbols into graphical documents is presented. More precisely, we propose a combined filtering and indexing mechanism that retrieves in an efficient way the most similar symbols to a given input query. For a database of 200000 symbols the retrieval time has been divided by a factor of 4, 5 compared to a linear search.","PeriodicalId":279268,"journal":{"name":"Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)","volume":"2014 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2007-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"15","resultStr":"{\"title\":\"An Indexing Method for Graphical Documents\",\"authors\":\"S. Tabbone, Daniel Zuwala\",\"doi\":\"10.1109/ICDAR.2007.55\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper, a method to browse symbols into graphical documents is presented. More precisely, we propose a combined filtering and indexing mechanism that retrieves in an efficient way the most similar symbols to a given input query. For a database of 200000 symbols the retrieval time has been divided by a factor of 4, 5 compared to a linear search.\",\"PeriodicalId\":279268,\"journal\":{\"name\":\"Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)\",\"volume\":\"2014 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-09-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"15\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDAR.2007.55\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Ninth International Conference on Document Analysis and Recognition (ICDAR 2007)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.2007.55","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper, a method to browse symbols into graphical documents is presented. More precisely, we propose a combined filtering and indexing mechanism that retrieves in an efficient way the most similar symbols to a given input query. For a database of 200000 symbols the retrieval time has been divided by a factor of 4, 5 compared to a linear search.