Diagram showing the process followed from the document-term matrices obtained by text mining to the building of sub-datasets containing the core information to characterize the technology fronts. The number of topics obtained for each time interval is shown.</p
1. Introduction to bringing structure to text 2. Mining phrase-based and entity-enriched topical hie...
This research aimed to integrate data mining and topic modeling for multi-document summarisation (MD...
Topic modeling is a method of statistically identifying abstract topics that are present throughout ...
Diagram showing the text-mining steps leading to obtaining the document-term matrices. This process ...
A summary of the topic modeling steps reported in accordance with Hickman et al.’s [88] best practic...
This chapter presents a method for analyzing text data called topic modeling and applying it to the ...
There is an increasing interest in automating creation of semantic structures, especially topic maps...
Increasingly, management researchers are using topic modeling, a new method borrowed from computer s...
Text contents are overloaded with the digitization of the data and new contents are transmitted thro...
Topic modeling is a machine learning technique that identifies latent topics in a text corpus. There...
This study investigates the evolution of information science research based on bibliometric analysis...
This study presents an innovative methodology for analysing technology news using various text minin...
Topic Modeling is a well-known unsupervised learning technique used when dealing with text data. It ...
It is estimated that the world’s data will increase to roughly 160 billion terabytes by 2025, with m...
Starting from text corpus analysis with linguistic and statistical analysis algorithms, an infrastru...
1. Introduction to bringing structure to text 2. Mining phrase-based and entity-enriched topical hie...
This research aimed to integrate data mining and topic modeling for multi-document summarisation (MD...
Topic modeling is a method of statistically identifying abstract topics that are present throughout ...
Diagram showing the text-mining steps leading to obtaining the document-term matrices. This process ...
A summary of the topic modeling steps reported in accordance with Hickman et al.’s [88] best practic...
This chapter presents a method for analyzing text data called topic modeling and applying it to the ...
There is an increasing interest in automating creation of semantic structures, especially topic maps...
Increasingly, management researchers are using topic modeling, a new method borrowed from computer s...
Text contents are overloaded with the digitization of the data and new contents are transmitted thro...
Topic modeling is a machine learning technique that identifies latent topics in a text corpus. There...
This study investigates the evolution of information science research based on bibliometric analysis...
This study presents an innovative methodology for analysing technology news using various text minin...
Topic Modeling is a well-known unsupervised learning technique used when dealing with text data. It ...
It is estimated that the world’s data will increase to roughly 160 billion terabytes by 2025, with m...
Starting from text corpus analysis with linguistic and statistical analysis algorithms, an infrastru...
1. Introduction to bringing structure to text 2. Mining phrase-based and entity-enriched topical hie...
This research aimed to integrate data mining and topic modeling for multi-document summarisation (MD...
Topic modeling is a method of statistically identifying abstract topics that are present throughout ...