Open AccessAn integrated model for discovering, classifying and labeling topics based on topic modeling
Author(s) -
Thanh Ho,
Phuc Do
Publication year - 2014
Publication title -
khoa học công nghệ
Language(s) - English
Resource type - Journals
ISSN - 1859-0128
DOI - 10.32508/stdj.v17i2.1361
Subject(s) - vietnamese , computer science , ontology , field (mathematics) , information retrieval , data modeling , artificial intelligence , topic model , data science , natural language processing , world wide web , database , linguistics , philosophy , mathematics , epistemology , pure mathematics
In this paper, we propose an integrated model for discovering, classifying and labeling topics of messages based on topic modeling to analyze and understand the topics of the messages posted by users on social networks. In which, the method of labeling is executed by machine learning on the training data and ontology. The ontology is created in the field of higher education. All parts of model are integrated on a system called social network analysis system based on topic modeling. The experiment of the model on the linguistic data of Vietnamese texts collected from a student forum is transformed into a data structure of social network, including: 13,208 messages by 2,494 users.