A massive number of news articles leads to the potential problem in automatic classification task. The discussions on classification of English news articles have been widely studied. However, it is in contrast to automatic classification of Indonesian news articles. The classification method that has been implemented is limited to conventional methods, such as Naïve Bayes and Support Vector Machine. Both methods is rigid in classify a document into one topic. Therefore, we implement one of Topic Modeling methods which represent a document as a distribution of topics and a topic is represented by a set of words. The method is Latent Dirichlet Allocation. The experimental stu...
Currently, exist a large amount of news in a digital format needs to be classified or labeled automa...
The amount of News displayed on online news portals. Often does not indicate the topic being discuss...
This work aims at discovering topics in a text corpus and classifying the most relevant terms for ea...
This paper is in the field of natural language processing. It applied unsupervised machine learning ...
Latent Dirichlet Allocation (LDA) is a probability model for grouping hidden topics in documents by ...
Innovations in Intelligent Systems and Applications Conference (ASYU) -- OCT 04-06, 2018 -- Adana, T...
Latent Dirichlet Allocation (LDA) is a widely implemented approach for extracting hidden topics in d...
Latent Dirichlet Allocation (LDA) is a probability model for grouping hidden topics in documents by ...
Recently, a probabilistic topic modelling approach, latent dirichlet allocation (LDA), has been exte...
The aim of this project is to explore the topic of Natural Language Processing and how to implement...
The amount of News displayed on online news portals. Often does not indicate the topic being discuss...
Automatic text categorization is one of the key techniques in information retrieval and the data min...
This work aims at discovering topics in a text corpus and classifying the most relevant terms for ea...
Much of human knowledge sits in large databases of unstructured text. Leveraging this knowledge requ...
Latent Dirichlet Allocation (LDA) is a widely implemented approach for extracting hidden topics in d...
Currently, exist a large amount of news in a digital format needs to be classified or labeled automa...
The amount of News displayed on online news portals. Often does not indicate the topic being discuss...
This work aims at discovering topics in a text corpus and classifying the most relevant terms for ea...
This paper is in the field of natural language processing. It applied unsupervised machine learning ...
Latent Dirichlet Allocation (LDA) is a probability model for grouping hidden topics in documents by ...
Innovations in Intelligent Systems and Applications Conference (ASYU) -- OCT 04-06, 2018 -- Adana, T...
Latent Dirichlet Allocation (LDA) is a widely implemented approach for extracting hidden topics in d...
Latent Dirichlet Allocation (LDA) is a probability model for grouping hidden topics in documents by ...
Recently, a probabilistic topic modelling approach, latent dirichlet allocation (LDA), has been exte...
The aim of this project is to explore the topic of Natural Language Processing and how to implement...
The amount of News displayed on online news portals. Often does not indicate the topic being discuss...
Automatic text categorization is one of the key techniques in information retrieval and the data min...
This work aims at discovering topics in a text corpus and classifying the most relevant terms for ea...
Much of human knowledge sits in large databases of unstructured text. Leveraging this knowledge requ...
Latent Dirichlet Allocation (LDA) is a widely implemented approach for extracting hidden topics in d...
Currently, exist a large amount of news in a digital format needs to be classified or labeled automa...
The amount of News displayed on online news portals. Often does not indicate the topic being discuss...
This work aims at discovering topics in a text corpus and classifying the most relevant terms for ea...