Using K-Means Algorithm for Description Analysis of Text in RSS News Format
This article shows the use of different techniques for the extraction of information through text mining. Through this implementation, the performance of each of the techniques in the dataset analysis process can be identified, which allows the reader to recommend the most appropriate technique for...
- Autores:
-
De-La-Hoz-Franco, Emiro
Oviedo Carrascal, Ana Isabel
Ariza Colpas, Paola Patricia
- Tipo de recurso:
- Article of journal
- Fecha de publicación:
- 2019
- Institución:
- Corporación Universidad de la Costa
- Repositorio:
- REDICUC - Repositorio CUC
- Idioma:
- eng
- OAI Identifier:
- oai:repositorio.cuc.edu.co:11323/7459
- Acceso en línea:
- https://hdl.handle.net/11323/7459
http://doi.org/10.1007/978-981-32-9563-6_17
https://repositorio.cuc.edu.co/
- Palabra clave:
- RSS news’s format
Simple K-means
Bag of words
Stopwords
Text mining
- Rights
- openAccess
- License
- Attribution-NonCommercial-NoDerivatives 4.0 International
| Summary: | This article shows the use of different techniques for the extraction of information through text mining. Through this implementation, the performance of each of the techniques in the dataset analysis process can be identified, which allows the reader to recommend the most appropriate technique for the processing of this type of data. This article shows the implementation of the K-means algorithm to determine the location of the news described in RSS format and the results of this type of grouping through a descriptive analysis of the resulting clusters. |
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