Add to ORKGThe article addresses the problem of document classification. A technology for automatic topic extraction from documents and application of the topics as document representation in classification task are described. The topics are understood as noun phrase-based main themes of documents. The suggested algorithm can also be used to improve the quality of automatic document clusterization
This thesis presents new methods for classification and thematic grouping of billions of web pages, ...
Increased advancement in a variety of study subjects and information technologies, has increased the...
This paper presents a novel methodology for topic ontology learning from text documents. The propose...
The article addresses the problem of document clusterization. The author describes a technology for ...
This bachelor's thesis deals with automatic document topic classification and provides a brief intro...
Feature extraction is one of the fundamental challenges in im-proving the accuracy of document class...
While automated methods for information organization have been around for several decades now, expon...
Topics extraction has become increasingly important due to its effectiveness in many tasks, includin...
Topic modeling is an unsupervised learning task that discovers the hidden topics in a ...
Abstract. In this paper, we review two techniques for topic discovery in collections of text documen...
In this paper, we introduce a new clustering algorithm for discovering and describing the topics com...
In the new age era, there is tons of information published on the web every day. Thus, it will take ...
Recently, a probabilistic topic modelling approach, latent dirichlet allocation (LDA), has been exte...
Topics extraction has become increasingly important due to its effectiveness in many tasks, includin...
Topics extraction from documents has become increasingly important due to its effectiveness in many ...
This thesis presents new methods for classification and thematic grouping of billions of web pages, ...
Increased advancement in a variety of study subjects and information technologies, has increased the...
This paper presents a novel methodology for topic ontology learning from text documents. The propose...
The article addresses the problem of document clusterization. The author describes a technology for ...
This bachelor's thesis deals with automatic document topic classification and provides a brief intro...
Feature extraction is one of the fundamental challenges in im-proving the accuracy of document class...
While automated methods for information organization have been around for several decades now, expon...
Topics extraction has become increasingly important due to its effectiveness in many tasks, includin...
Topic modeling is an unsupervised learning task that discovers the hidden topics in a ...
Abstract. In this paper, we review two techniques for topic discovery in collections of text documen...
In this paper, we introduce a new clustering algorithm for discovering and describing the topics com...
In the new age era, there is tons of information published on the web every day. Thus, it will take ...
Recently, a probabilistic topic modelling approach, latent dirichlet allocation (LDA), has been exte...
Topics extraction has become increasingly important due to its effectiveness in many tasks, includin...
Topics extraction from documents has become increasingly important due to its effectiveness in many ...
This thesis presents new methods for classification and thematic grouping of billions of web pages, ...
Increased advancement in a variety of study subjects and information technologies, has increased the...
This paper presents a novel methodology for topic ontology learning from text documents. The propose...