A semi-structured document has more structured information compared to an ordinary document, and the relation among semi-structured documents can be fully utilized. In order to take advantage of the structure and link information in a semi-structured document for better mining, a structured link vector model (SLVM) is presented in this paper, where a vector represents a document, and vectors' elements are determined by terms, document structure and neighboring documents. Text mining based on SLVM is described in the procedure of K-means for briefness and clarity: calculating document similarity and calculating cluster center. The clustering based on SLVM performs significantly better than that based on a conventional vector space model...
Abstract: Most of the common techniques of text mining are based on the statistical analysis of the ...
The text is nothing but the combination of characters. Therefore, analyzing and extracting informati...
Abstract:Most of the common techniques of text mining are based on the statistical analysis of the t...
XML has become main data format in e-Business, e-Learning, e-Commerce, the need for tools to help ma...
Capturing latent structural and semantic properties in semi-structured documents (e.g., XML document...
A quick growth of internet technology makes it easy to assemble a huge volume of data as text docume...
AbstractThe number of semi-structured documents that is produced is steadily increasing. Thus, it wi...
Structured link vector model (SLVM) is a representation proposed for modeling XML documents which wa...
Evidently there is a tremendous proliferation in the amount of information found today on the larges...
The rapid growth of XML adoption has urged for the need of a proper representation for semi-structur...
This paper describes a text mining tool that performs two tasks, namely document clustering and text...
We explore a matrix-space model, that is a natural extension to the vector space model for Informati...
Most of text mining techniques are based on word and/or phrase analysis of the text. The statistical...
In this work, we jointly apply several text mining methods to a corpus of legal documents in order t...
Abstract: Text-mining methods have become a key feature for homeland-security technologies, as they ...
Abstract: Most of the common techniques of text mining are based on the statistical analysis of the ...
The text is nothing but the combination of characters. Therefore, analyzing and extracting informati...
Abstract:Most of the common techniques of text mining are based on the statistical analysis of the t...
XML has become main data format in e-Business, e-Learning, e-Commerce, the need for tools to help ma...
Capturing latent structural and semantic properties in semi-structured documents (e.g., XML document...
A quick growth of internet technology makes it easy to assemble a huge volume of data as text docume...
AbstractThe number of semi-structured documents that is produced is steadily increasing. Thus, it wi...
Structured link vector model (SLVM) is a representation proposed for modeling XML documents which wa...
Evidently there is a tremendous proliferation in the amount of information found today on the larges...
The rapid growth of XML adoption has urged for the need of a proper representation for semi-structur...
This paper describes a text mining tool that performs two tasks, namely document clustering and text...
We explore a matrix-space model, that is a natural extension to the vector space model for Informati...
Most of text mining techniques are based on word and/or phrase analysis of the text. The statistical...
In this work, we jointly apply several text mining methods to a corpus of legal documents in order t...
Abstract: Text-mining methods have become a key feature for homeland-security technologies, as they ...
Abstract: Most of the common techniques of text mining are based on the statistical analysis of the ...
The text is nothing but the combination of characters. Therefore, analyzing and extracting informati...
Abstract:Most of the common techniques of text mining are based on the statistical analysis of the t...