DOCUMENT CLASSIFICATION Combining Structure and Content
Technical documentation such as user manual and manufacturing document is now an important part of the industrial production. Indeed, without such documents, the products can neither be manufactured nor used according to their complexity. Therefore, the increasing volume of such documents stored in the electronic format, needs an automatic classification system in order to categorize them in pre-defined classes and to retrieve the information quickly. On the other hand, these documents are strongly structured and contain the elements like tables and schemas. However, the traditional document classification typically classifies the documents considering the document text and ignoring its structural elements. In this paper, we propose a method which makes use of structural elements to create the document feature vector for classification. A feature in this vector is a combination of the term and the structure. The document structure is represented by the tags of the XML document. The SVM algorithm has been used as learning and classifying algorithm.
Document classification Document structure Technical document Support vector machine Vector space
Samaneh Chagheri Sylvie Calabretto Catherine Roussey Cyril Dumoulin
Université de Lyon, CNRS, LIRIS UMR 5205, INSA de Lyon, 7 Avenue Jean Capelle, Villeurbanne, France Cemagref, Campus des Cézeaux, Clermont Ferrand, 24 Avenue des Landais, Aubière, France 27, rue Lucien Langénieux, Roanne, France
国际会议
13th International Conference on Enterprise Information System(第13届企业信息系统国际会议 ICEIS 2011)
北京
英文
1984-1989
2011-06-08（万方平台首次上网日期，不代表论文的发表时间）