A Novel Approach to Categorize News Articles From Headlines and Short Text

2020 IEEE Region 10 Symposium (TENSYMP)(2020)

引用 0|浏览0
暂无评分
摘要
Over the last few years the world has experienced a surge in the number of online news portals. This has caused the volume of news articles to reach an all time high; which will only get higher with time. Thus, an efficient system of categorization and organization of the articles has become a necessity for various information systems like- news aggregation and association in search engines. It is impractical to employ humans to label this expansive volume of text data, prompting the growth of automated text categorization systems. And so, we devised a deep learning model that effectively categorizes news articles from the headlines and short text descriptions. The prime foci of our work were to design, develop, and measure the performance metrics of our proposed model.
更多
查看译文
关键词
NLP,Short text classification,Deep Learning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要