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@article{174014,
        author = {Prof. Ghadge S. V. and Prof. Shah Saloni Niranjan and Kiran Narute and Aditya Ranaware and Saurav Nagawade},
        title = {A Survey on Text Summarization Of News Articles Using Natural Language Processing},
        journal = {International Journal of Innovative Research in Technology},
        year = {2025},
        volume = {11},
        number = {10},
        pages = {2390-2393},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=174014},
        abstract = {This approach utilizing PageRank algorithm for summarization is in fact extractive in nature and takes inspiration from the original rank ordering done by Google. Given the exponential increase in load of news, summarization has become the need of the hour to make a quick understanding about significant information. The process involves preprocessing along with embedding the sentences through Word2Vec, followed by capturing real important points and ranking them up using PageRank. The results show that this technique well extracts and ranks important sentences concisely without compromising on the theme; hence, suitable for real-time media applications.},
        keywords = {Text Summarization,PageRank, Extractive Summarization, News Summarization, Word2Vec, Sentence Ranking, NLP.},
        month = {March},
        }