The project specializes in Text Summarization using NLP's SpaCy and NLTK extractive approach, preserving key information for concise summaries. Customize length, handle various formats, and enjoy a user-friendly interface. Applications include document skimming, content aggregation, and data analysis. Hop in to simplify information consumption! 🚀
Key Features: This summarization system is powered by advanced Natural Language Processing (NLP) algorithms and models. Through this, we can effectively identify and extract the most salient sentences, retaining the essence of the original text in the summary. Additionally, users can customize the length of the summary based on their preferences, whether they need a brief overview or a more comprehensive synopsis. To achieve this, I've simply utilized the top 08 sentences after calculating their frequency and maintaining a dictionary. This process guarantees that the most relevant and significant information is retained in the summary.
Furthermore, the system boasts robust preprocessing capabilities, efficiently handling various text formats and eliminating noise and irrelevant content. This results in polished and coherent summaries, ensuring the extracted information is accurate and meaningful.
I offered a user-friendly interface, powered by Streamlit, that simplifies the text summarization process for all individuals. Whether you are an NLP expert or a novice, the intuitive interface makes text summarization effortless and accessible.
How to Use: Using the platform is straightforward. Users need to input the text they wish to summarize into the interface. They can then choose their preferred summarization procedure, either through Spacy or NLTK. By clicking the 'Summarize' button, a concise and accurate summary of the input text is generated. Users can easily copy the generated summary to their clipboard or directly share it with others.