This paper describes the approach taken to the XML Mining track at INEX 2008 by a group at the Queensland University of Technology. We introduce the K-tree clustering algorithm in an Information Retrieval context by adapting it for document clustering. Many large scale problems exist in document clustering. K-tree scales well with large inputs due to its low complexity. It offers promising results both in terms of efficiency and quality. Document classification was completed using Support Vector Machines
XML has become main data format in e-Business, e-Learning, e-Commerce, the need for tools to help ma...
Increased advancement in a variety of study subjects and information technologies, has increased the...
The purpose of text clustering in information retrieval is to discover groups of semantically relate...
This paper reports on the experiments and results of a clustering approach used in the INEX 2008 doc...
The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problem...
In the last few years we have observed a proliferation of approaches for clustering XML documents an...
Documents Clustering is a technique in which relationships between sets of documents are being autom...
In this paper, we first employ the well known Cover-Coefficient Based Clustering Methodology (C3M) f...
In the last few years we have observed a proliferation of approaches for clustering XML docu- ments ...
As document searching becomes more and more important with the rapid growth of document bases today,...
International audienceThis article is a report concerning the two years of the XML Mining track at I...
In today’s era of World Wide Web, there is a tremendous proliferation in the amount of...
Since the amount of text data stored in computer repositories is growing every day, we need more tha...
Data mining, also known as knowledge discovery in database (KDD), is the process to discover interes...
Document clustering, which is also refered to as text clustering, is a technique of unsupervised doc...
XML has become main data format in e-Business, e-Learning, e-Commerce, the need for tools to help ma...
Increased advancement in a variety of study subjects and information technologies, has increased the...
The purpose of text clustering in information retrieval is to discover groups of semantically relate...
This paper reports on the experiments and results of a clustering approach used in the INEX 2008 doc...
The XML Document Mining track was launched for exploring two main ideas: (1) identifying key problem...
In the last few years we have observed a proliferation of approaches for clustering XML documents an...
Documents Clustering is a technique in which relationships between sets of documents are being autom...
In this paper, we first employ the well known Cover-Coefficient Based Clustering Methodology (C3M) f...
In the last few years we have observed a proliferation of approaches for clustering XML docu- ments ...
As document searching becomes more and more important with the rapid growth of document bases today,...
International audienceThis article is a report concerning the two years of the XML Mining track at I...
In today’s era of World Wide Web, there is a tremendous proliferation in the amount of...
Since the amount of text data stored in computer repositories is growing every day, we need more tha...
Data mining, also known as knowledge discovery in database (KDD), is the process to discover interes...
Document clustering, which is also refered to as text clustering, is a technique of unsupervised doc...
XML has become main data format in e-Business, e-Learning, e-Commerce, the need for tools to help ma...
Increased advancement in a variety of study subjects and information technologies, has increased the...
The purpose of text clustering in information retrieval is to discover groups of semantically relate...