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eversvd,+8 (9)

Kangan Maria, Prof. Sridhar Ranganathan

2026eninformation extractiontext summarizationweb scrapingnewspapersnatural language processingsearch enginetext extractioninformation retrievalnlpuser interface

Abstract

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The vast expanse of the web contains tens of millions of documents spanning various subjects, making it challenging for individuals to sift through vast amounts of data to gain knowledge on specific topics. This research aims to develop an information extraction system specifically designed for tracking subject matter from English newspapers. The methodology involves creating a user-friendly interface that allows users to interact with the application seamlessly. This system is engineered to extract relevant information from various sources, such as online articles and newspaper content, while filtering out irrelevant elements like advertisements and user comments. By employing advanced techniques in text extraction and information retrieval, this system focuses on gathering and summarizing important data, presenting it in a coherent format conducive for user comprehension. Ultimately, the findings illustrate that the proposed framework not only meets the information retrieval needs of users but also provides them with a comprehensive understanding of current events across multiple platforms, thereby enhancing their overall access to pertinent news data.

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Cite This Work

@article{5d2d233d-199a-4a08-8aac-041f6bdbf48d,
  title={eversvd,+8 (9)},
  author={Kangan Maria and Prof. Sridhar Ranganathan},
  year={2026},
  language={en}
}
TY  - JOUR
TI  - eversvd,+8 (9)
AU  - Kangan Maria
AU  - Prof. Sridhar Ranganathan
PY  - 2026
LA  - en
ER  -

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