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《Journal of Beijing Information Science & Technology University》 2019-01
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Reflowable document comprehension method based on fusion features and grammar rules

HAO Haili;LI Ning;TIAN Ying′ai;GENG Si;Computer School,Beijing Information Science & Technology University;  
In order to achieve adequate component identification in reflowable document structure understanding, a new method to understand documents is proposed based on fusion features and grammatical rules. Two vectors are used in the method. One is the format vector representing the format features, such as fonts; the other is the content vector representing text features such as keywords. Then the components to be identified are compared with the candidates by measuring the distance between the vectors with different weights. Finally, based on the candidate labels and grammatical rules, the logic structure of the document is recognized by applying the top-down and bottom-up algorithm. The experiment results show that this method can effectively improve the accuracy of component identification, and in turn improve the accuracy of whole document structure recognition.
【Fund】: 国家重点研发计划项目(2018YFB1004100);; 国家自然科学基金资助项目(61672105)
【CateGory Index】: TP391.1
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