SqueezeNews 📖
In today's modern society, a large amount of news is poured out in various fields such as politics, the economy, and society. There is no time to read all these vast amounts of news accumulated every day. A function that summarizes only the core of the article and shows it at a glance can save time for busy modern people and it will help them easily identify trends.
Dependencies 🌏
Mission Statement 📝
The ‘SqueezeNews’ project develops open-source software for extracting and curating articles. The ‘SqueezeNews’ allows for extracting articles using python web-crawling. It is designed to easily bring up the full text and keywords of news articles. Also, it provides various visual data(e.g. word cloud, graphs) according to the frequency of keywords.
Feature List 📋
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Brings up the full text of news articles.
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Summarizes articles and extracting keywords.
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(planned) Creates a word cloud according to the frequency of keywords.
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(planned) Search for similar articles.
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(planned) Analysis of news article tendency according to positive or negative word ratio.
Target Development Language
Python .
How to use ✍️
1. Clone GitHub repository
https://github.com/rmakerck37/SqueezeNews.git
2. Install Dependencies
pip install -r requirements.txt
3. Run code
- Get urls
import news_url_import
keyword = '금값'
num = 10
dictUrl = news_url_import.news_url_import(keyword, num)- Get article texts
import news_text
url = dictUrl[0]['url']
myText = news_text.text_extraction(url)
print(myText)- Get keywords
import news_keyword
myKeyword = news_keyword.get_keyword(url,'ko')
print(myKeyword)- Summarizing news
import news_summarization
mySummary = news_summarization.summarize(text=myText, max_sents=5)
License 🚩
Copyright © 2021 rmakerck37.
This project is available under the Apache-2.0 License.
