Add to ORKGAbstract: In this paper we present a system which automatically converts text documents into XML by extracting information from previously tagged XML documents. The system uses the Self-Organizing Map (SOM) learning algorithm to arrange tagged documents on a two-dimensional map such that nearby locations contain similar documents. It then employs an inductive learning algorithm to automatically extract and apply auto-tagging rules from the nearest SOM neighbours of an untagged document. The system is designed to be adaptive, so that once a document is tagged in XML, it learns from its errors in order to improve accuracy. The automatically tagged documents can subsequently be categorized on the Self-Organizing Map, further improving the map&...
In this paper we investigate the use of Self-Organising Maps (SOM) for document clustering. Previous...
International audienceWe address the problem of learning to map automatically flat and semi-structur...
The Self-Organising Map (SOM) is widely used to classify document collections. Such classifications ...
In this paper we present a novel system which automatically converts text documents into XML by extr...
We present a novel system for automatically marking up text documents into XML and discuss the benef...
In this paper we present a novel system for automatically marking up text documents into XML. The sy...
In this paper we present a novel system that can automatically mark up text documents into XML. The ...
We introduce a novel two-stage automatic XML mark-up system, which combines the WEBSOM approach to ...
The number of XML documents produced and available on the Internet is steadily increasing. It is thu...
Self-Organizing Maps capable of encoding structured information will be used for the clustering of X...
Self-Organizing Maps capable of encoding structured information will be used for the clustering of X...
This thesis explored and visualized the relationships of documents data, based on the technique of s...
In this paper, neural network techniques based on Kohonen\u2019s self-organising map method which ca...
In this paper we investigate the use of Self-Organising Maps (SOM) for document clustering. Previous...
International audienceWe address the problem of learning to map automatically flat and semi-structur...
The Self-Organising Map (SOM) is widely used to classify document collections. Such classifications ...
In this paper we present a novel system which automatically converts text documents into XML by extr...
We present a novel system for automatically marking up text documents into XML and discuss the benef...
In this paper we present a novel system for automatically marking up text documents into XML. The sy...
In this paper we present a novel system that can automatically mark up text documents into XML. The ...
We introduce a novel two-stage automatic XML mark-up system, which combines the WEBSOM approach to ...
The number of XML documents produced and available on the Internet is steadily increasing. It is thu...
Self-Organizing Maps capable of encoding structured information will be used for the clustering of X...
Self-Organizing Maps capable of encoding structured information will be used for the clustering of X...
This thesis explored and visualized the relationships of documents data, based on the technique of s...
In this paper, neural network techniques based on Kohonen\u2019s self-organising map method which ca...
In this paper we investigate the use of Self-Organising Maps (SOM) for document clustering. Previous...
International audienceWe address the problem of learning to map automatically flat and semi-structur...
The Self-Organising Map (SOM) is widely used to classify document collections. Such classifications ...