The project goal is to use existing labels and supervised learning to classify groups. The labels of these groups can also be regarded as the labels of the articles in the group, because the manual labeling is also determined according to the topic of the articles in the group. Some machine learning models, such as Lightgbm anf XGBoost, are used in this project when training and predicting labels.

The project goal is to use existing labels and supervised learning to classify groups. The labels of these groups can also be regarded as the labels of the articles in the group, because the manual labeling is also determined according to the topic of the articles in the group. Some machine learning models, such as Lightgbm anf XGBoost, are used in this project when training and predicting labels.

Classifying community text and community groups using machine learning

HUANG, ZESEN
2021/2022

Abstract

The project goal is to use existing labels and supervised learning to classify groups. The labels of these groups can also be regarded as the labels of the articles in the group, because the manual labeling is also determined according to the topic of the articles in the group. Some machine learning models, such as Lightgbm anf XGBoost, are used in this project when training and predicting labels.
2021
Classifying community text and community groups using machine learning
The project goal is to use existing labels and supervised learning to classify groups. The labels of these groups can also be regarded as the labels of the articles in the group, because the manual labeling is also determined according to the topic of the articles in the group. Some machine learning models, such as Lightgbm anf XGBoost, are used in this project when training and predicting labels.
machine learning
text classification
NLP
File in questo prodotto:
File Dimensione Formato  
Classifying community text and community groups using machine learning.pdf

accesso aperto

Dimensione 3.6 MB
Formato Adobe PDF
3.6 MB Adobe PDF Visualizza/Apri

The text of this website © Università degli studi di Padova. Full Text are published under a non-exclusive license. Metadata are under a CC0 License

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12608/42065