Add to ORKGA language-independent method for automatic clustering of certain classes of documents is described. No training or information external to the document contents is required. The method is based on a form of single-linkage clustering in which a real-valued dissimilarity measure is defined for pairs of documents and the document set is considered as a complete weighted graph whose edge weights are given by the dissimilarity measure. A minimum spanning tree is constructed on this graph and it is processed to construct a clustering. The results of testing and evaluation are discussed
Documents Clustering is a technique in which relationships between sets of documents are being autom...
Abstract: Clustering is a technique of collecting data into subsets in such a manner that identical ...
This report proposes a novel unsupervised document clustering approach based on weighted combination...
In text mining, document clustering describes the efforts to assign unstructured documents to cluste...
Document clustering, which is also refered to as text clustering, is a technique of unsupervised doc...
Document clustering is text processing that groups documents with similar concept. Clustering is def...
Abstract: Clustering is the problem of discovering “meaningful ” groups in given data. The first and...
This paper discusses a new type of semi-supervised docu-ment clustering that uses partial supervisio...
In the last times, semi-supervised clustering has been an area that has received a lot of attention....
This technical report addresses the problem of automatically structuring linked document collections...
Abstract Background In text mining, document clustering describes the efforts to assign unstructured...
This paper addresses the problem of automatically structuring linked document collections by using c...
Document clustering is a process of grouping documents into several natural and homogeneous clusters...
Nowadays, the explosive growth in text data emphasizes the need for developing new and computational...
We present a novel implementation of the recently introduced information bottleneck method for unsup...
Documents Clustering is a technique in which relationships between sets of documents are being autom...
Abstract: Clustering is a technique of collecting data into subsets in such a manner that identical ...
This report proposes a novel unsupervised document clustering approach based on weighted combination...
In text mining, document clustering describes the efforts to assign unstructured documents to cluste...
Document clustering, which is also refered to as text clustering, is a technique of unsupervised doc...
Document clustering is text processing that groups documents with similar concept. Clustering is def...
Abstract: Clustering is the problem of discovering “meaningful ” groups in given data. The first and...
This paper discusses a new type of semi-supervised docu-ment clustering that uses partial supervisio...
In the last times, semi-supervised clustering has been an area that has received a lot of attention....
This technical report addresses the problem of automatically structuring linked document collections...
Abstract Background In text mining, document clustering describes the efforts to assign unstructured...
This paper addresses the problem of automatically structuring linked document collections by using c...
Document clustering is a process of grouping documents into several natural and homogeneous clusters...
Nowadays, the explosive growth in text data emphasizes the need for developing new and computational...
We present a novel implementation of the recently introduced information bottleneck method for unsup...
Documents Clustering is a technique in which relationships between sets of documents are being autom...
Abstract: Clustering is a technique of collecting data into subsets in such a manner that identical ...
This report proposes a novel unsupervised document clustering approach based on weighted combination...