caa a22 4500 445379499 CHVBK 20180317143013.0 cr unu---uuuuu 170323e20110301xx s 000 0 eng 10.1007/s10032-010-0144-2 doi (NATIONALLICENCE)springer-10.1007/s10032-010-0144-2 Silva Ana The Informatics Forum, Centre for Intelligent Systems and their Applications, School of Informatics, The University of Edinburgh, 10 Crichton Street, EH8 9AB, Edinburgh, Scotland, UK aut Metrics for evaluating performance in document analysis: application to tables [Elektronische Daten] [Ana Silva] Is an algorithm with high precision and recall at identifying table-parts also good at locating tables? Several document analysis tasks require merging or splitting certain document elements to form others. The suitability of the commonly used precision and recall for such division/aggregation tasks is arguable, since their underlying assumption is that the granularity of the items at input is the same as at output. We propose a new pair of evaluation metrics that better suit document analysis' needs and show their application to several table tasks. In the process, we present a number of robust table location algorithms with which we draw a road-map for creating Hidden Markov Models for the task. Springer-Verlag, 2011 Performance evaluation nationallicence Document analysis nationallicence Table processing nationallicence Metrics nationallicence International Journal on Document Analysis and Recognition (IJDAR) Springer-Verlag 14/1(2011-03-01), 101-109 1433-2833 14:1<101 2011 14 10032 https://doi.org/10.1007/s10032-010-0144-2 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10032-010-0144-2 text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Silva Ana The Informatics Forum, Centre for Intelligent Systems and their Applications, School of Informatics, The University of Edinburgh, 10 Crichton Street, EH8 9AB, Edinburgh, Scotland, UK aut NATIONALLICENCE 773 0- International Journal on Document Analysis and Recognition (IJDAR) Springer-Verlag 14/1(2011-03-01), 101-109 1433-2833 14:1<101 2011 14 10032 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer