Appdated An Application Categorizing Bicol Related News Articles

This application identifies topics in Bicol-related news articles through the use of generated clustered models.

External Libraries Used:

1. Beautiful Soup 4
2. Scikit-learn
3. matplotlib
4. pandas
5. NumPy
6. requests

Main Algorithms Used

• TFIDF

• K-Means++

Purpose of the Algorithms

1. TFIDF:

This algorithm is used to process textual data to numerical data as the Scikit-Learn library only accepts numerical data as a model.

2. K-Means++:

This algorithm is responsible for clustering the data generated by the TFIDF algorithm. The main reason on why we used clustering instead of a classifier is that we do not know what exactly is in the data.

Screenshots

(To be added later)

Main Features

1. Tkinter graphical user interface
2. Collect news data from Rappler and Inquirer
3. Edit Cluster Labels
4. View Cluster Contents
5. Import Cluster Model
6. View Graph (Scatterplot and Line Graph)

Authors

• Glenn Matthew Perez

• Steven Clien Ramos

• Angelo Duran

(More details to be added soon)