{"title":"Layout and language: preliminary investigations in recognizing the structure of tables","authors":"Matthew F. Hurst, Shona Douglas","doi":"10.1109/ICDAR.1997.620668","DOIUrl":null,"url":null,"abstract":"Describes a prototype system for assigning table cells to their proper place in the logical structure of the table, based on a simple model of table structure combined with a number of measures of cohesion between cells. A framework is presented for examining the effect of particular variables on the performance of the system, and preliminary results are presented showing the effect of cohesion measures based on the simplest domain-independent analyses, with the aim allowing future comparison with more knowledge-intensive analyses based on natural language processing. These baseline results suggest that very simple string-based cohesion measures are not sufficient to support the extraction of tuples as we require. Future work will pursue the aim of more adequate approximations to a notional subtype/supertype definition of the relationship between value cells and label cells.","PeriodicalId":435320,"journal":{"name":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-08-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"42","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Fourth International Conference on Document Analysis and Recognition","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDAR.1997.620668","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 42
Abstract
Describes a prototype system for assigning table cells to their proper place in the logical structure of the table, based on a simple model of table structure combined with a number of measures of cohesion between cells. A framework is presented for examining the effect of particular variables on the performance of the system, and preliminary results are presented showing the effect of cohesion measures based on the simplest domain-independent analyses, with the aim allowing future comparison with more knowledge-intensive analyses based on natural language processing. These baseline results suggest that very simple string-based cohesion measures are not sufficient to support the extraction of tuples as we require. Future work will pursue the aim of more adequate approximations to a notional subtype/supertype definition of the relationship between value cells and label cells.