Generating Document Summary using Data Mining and Clustering Techniques

نویسندگان

چکیده


 Abstract
 This paper presents a novel approach to generating document summaries using data mining and clustering techniques, specifically K-means bisecting algorithms. With the exponential growth of textual data, there is an increasing need for efficient accurate summarization techniques aid users in understanding key information within large collections documents. study explores potential methods extracting salient features from producing high-quality summaries. By applying algorithms preprocessed proposed groups similar sentences together selects most representative each cluster form final summary. The performance method evaluated standard evaluation metrics, such as precision, recall, F1-score, compared with existing techniques. results demonstrate that combination provides promising solution concise summaries, applications various domains, news aggregation, scientific literature summarization, social media content analysis.

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ژورنال

عنوان ژورنال: The Philippine statistician (Quezon City)

سال: 2021

ISSN: ['2094-0343']

DOI: https://doi.org/10.17762/msea.v70i1.2310