OpenCraft24-Summify

# Project Name: Summify

This innovative project combines two powerful tools: a web app for comprehensive keyword-based article discovery and summarization, and a browser extension for seamless on-page summarization. With intuitive interfaces and intelligent processing, it empowers users to explore information efficiently and gain insights effortlessly.

Check out this video demonstration of the project: Project Demo.

Key Features:

• Intuitive Web App:
  • Effortless Autocomplete: Ensures fast and accurate keyword exploration.
  • Relevant Article Discovery: Leverages powerful search algorithms to surface the most pertinent articles from a vast dataset.
  • Direct Article Access: Seamlessly opens articles in browser tabs for in-depth reading.
• Powerful Summarization Extension:
  • One-Click Summarization: Instantly summarizes webpages on the current tab, saving valuable time.
  • Customizable Length: Tailors summaries to fit individual needs and preferences.
  • Advanced Scraping: Extracts key textual content for accurate summarization.
  • Related Article Suggestions: Offers further exploration based on summarized content.

Workflow:

1. Web App:
   • Enter a keyword or phrase.
   • Enjoy autocomplete suggestions for faster exploration.
   • Discover relevant articles from the comprehensive dataset.
   • Click on an article to open it directly in your browser.
2. Summarization Extension (for Chrome/Firefox):
   • Install the extension in your browser.
   • Navigate to an article or webpage.
   • Click the extension's icon to initiate summarization.
   • Specify the desired summary length (optional).
   • Review the concise summary, highlighting key points.
   • Explore suggested related articles for deeper understanding.

Technical Details:

• Web App:
  • Programming language: [e.g., Python, JavaScript]
  • Framework: [e.g., Flask, Django, js]
  • Dataset source: [e.g., Global-News-Dataset, one that was present under the problem statement]
• Summarization Extension:
  • Provides the feature of changing the length of the summarizer.
  • Summarization that is not just ranking the top sentenses but rephrasing the entire content to meet the user's need.
  • Related article suggestion

Code Example (Keyword Processing):

def process_text(text):Summarizer extension
    """Process text function.
    Input:
        text: a string containing the text
    Output:
        processed_text: a list of words containing the processed text

    """
    stemmer = PorterStemmer()
    stopwords_english = stopwords.words('english')

    # remove stock market tickers like $GE
    text = re.sub(r'\$\w*', '', text)
    # remove old style retweet text "RT"
    text = re.sub(r'^RT[\s]+', '', text)
    # remove hyperlinks    
    text = re.sub(r'https?://[^\s\n\r]+', '', text)
    # remove hashtags
    # only removing the hash # sign from the word
    text = re.sub(r'#', '', text)
    # tokenize text
    tokenizer = TweetTokenizer(preserve_case=False, strip_handles=True,
                               reduce_len=True)
    text_tokens = tokenizer.tokenize(text)

    processed_text = []
    for word in text_tokens:
        if (word not in stopwords_english and  # remove stopwords
                word not in string.punctuation):  # remove punctuation
            # processed_text.append(word)
            stem_word = stemmer.stem(word)  # stemming word
            processed_text.append(stem_word)

    return processed_text

Screenshots:

Updated Screenshots

This update merged the functionalities of the webapp into the extension and this is how it looks like

GitHub Repositories:

• Web App: Webapp
• Summarization Extension: extension

Benefits:

• Enhanced Research Efficiency: Find exactly what you need quickly and easily.
• Deeper Understanding: Summarize complex information for effortless knowledge gain.
• Time-Saving Convenience: Seamless integration and one-click summarization.
• Customizable Experience: Tailored summaries to fit your needs.