Graphical Document Representation for French Newsletters Analysis

被引:0
|
作者
Blandin, Alexis [1 ,2 ]
Said, Farida [3 ]
Villaneau, Jeanne [4 ]
Marteau, Pierre-Francois [1 ]
机构
[1] IRISA Univ Bretagne Sud, Vannes, France
[2] Kosmopolead UNEEK, Nantes, France
[3] LMBA Univ Bretagne Sud, Lorient, France
[4] IRISA Univ Bretagne Sud, Lorient, France
关键词
Newsletter; Dataset; Graph embedding; Graph convolutional network; TIME;
D O I
10.1145/3558100.3563856
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Document analysis is essential in many industrial applications. However, engineering natural language resources to represent entire documents is still challenging. Besides, available resources in French are scarce and do not cover all possible tasks, especially in specific business applications. In this context, we present a French newsletter dataset and its use to predict the good or bad impact of newsletters on readers. We propose a new representation of newsletters in the form of graphs that consider the newsletters' layout. We evaluate the relevance of the proposed representation to predict a newsletter's performance in terms of open and click rates using graph analysis methods.
引用
收藏
页数:8
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