Improvised Clarity-cuts Text Summarization with Text to Graph Prediction

Computer Science Engineering

The project titled "Improvised Text Summarization and Text-to-Graph Prediction" aims to develop an advanced text summarization system that enhances the extraction and representation of key information from large text corpora. This system leverages the integration of natural language processing (NLP) techniques and graph theory to produce more coherent and contextually relevant summaries. The approach involves several key steps: preprocessing the text to tokenize and clean the data, extracting significant keywords using methods like Transform model,TF-IDF and RAKE, and constructing a graph where nodes represent these keywords and edges represent their relationships based on co-occurrence and semantic similarity. Centrality measures and community detection algorithms are applied to the graph to identify the most important nodes and clusters of related concepts. Sentences containing these key nodes are then selected and ranked using graph-based algorithms like PageRank to generate the final summary. By transforming the text into a graph structure, this method captures the intricate relationships between concepts more effectively than traditional linear summarization techniques. This not only improves the quality and relevance of the summaries but also provides a visual and analytical representation of the underlying structure of the text. The system is implemented using advanced NLP tools and libraries such as NLTK, Spacy, and NetworkX, and it utilizes transformer models like BERT and GPT for enhanced keyword extraction and sentence ranking. This project has significant applications in various domains such as information retrieval, content management, and data analysis, where efficient and accurate summarization of large volumes of text is crucial. The improvised method demonstrates the potential to revolutionize how text data is summarized and interpreted, offering a powerful tool for both academic research and practical applications.

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