text summarization
- 1. TEXT SUMMARIZATION Presented by: OM PATEL(19012011026) AKSHAT PATEL(19012011106)
- 3. Problem Definition Everyone in today's technology-driven society has to produce some kind of document online, whether it's a presentation, documentation, or even email. We often see that students need to produce large pdf files in front of their universities or colleges. The text contained in them sometimes becomes too lengthy and too hard to understand. Despite the immense resources accessible on the internet, getting through those large chunks of text can be highly perplexing for the user. Natural language along with machine learning processing made it simpler to summarise lengthy amounts of text into a cohesive and fluent summary that only includes the document's important ideas.
- 4. Model used in project NLP (Natural Language Processing) Natural language processing (NLP) is a field that focuses on making natural human language usable by computer programs. NLTK, or Natural Language Toolkit, is a Python package that you can use for NLP. A lot of the data that you could be analyzing is unstructured data and contains human-readable text.
- 5. Text Sumarization techniques Text summarization can broadly be divided into two categories — Extractive Summarization and Abstractive Summarization. 1. Extractive Summarization: These methods rely on extracting several parts, such as phrases and sentences, from a piece of text and stack them together to create a summary. Therefore, identifying the right sentences for summarization is of utmost importance in an extractive method. 2. Abstractive Summarization: These methods use advanced NLP techniques to generate an entirely new summary. Some parts of this summary may not even appear in the original text.
- 6. Tools and Technology used in this project. TOOLS Spyder/pycharm TECHNOLOGIES nlp-Machine learning LANGUAGE Python
- 7. PROTOTYPE
- 8. Conclusion Text summarization is the process of condensing large amounts of information into concise, consumable texts. It helps readers understand complex topics quickly by reducing the topics down to their main points. Text Summarization has become an important part in today’s world due to its necessity. Creating an effiicient and accurate text summarizer is our goal.