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Updated: Oct 26, 2025

A Knowledge Graph Approach to Elucidate the Role of Organellar Pathways in Disease via Biomedical Reports
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Word synonym relationships for text analysis: A graph-based approach.

Hend Alrasheed1

  • 1Department of Information Technology, College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia.

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PubMed
Summary

This study introduces an unsupervised graph-based method for keyword extraction. The approach effectively identifies key terms and analyzes topic diversity without requiring user input, outperforming other techniques.

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Area of Science:

  • Natural Language Processing
  • Text Mining
  • Graph Analysis

Background:

  • Keyword extraction is crucial for information retrieval tasks like summarization and categorization.
  • Graph-based methods offer advantages in capturing text structure over traditional techniques.
  • The need for efficient, unsupervised keyword extraction methods is growing.

Purpose of the Study:

  • To propose a simple, unsupervised text mining approach for keyword extraction.
  • To analyze topic diversity and sentiment using extracted keywords.
  • To develop a method that groups semantically similar words for comprehensive keyword sets.

Main Methods:

  • Representing text as a directed graph based on synonym relationships.
  • Employing community detection and graph analysis for keyword identification.
  • Utilizing extracted keywords for topic diversity and sentiment analysis.

Main Results:

  • The proposed unsupervised approach effectively extracts keywords.
  • The method successfully assesses topic diversity and sentiment.
  • Achieved significant results compared to existing keyword extraction techniques.

Conclusions:

  • The unsupervised graph-based method provides a comprehensive and efficient approach to keyword extraction.
  • The technique enhances text analysis by assessing topic diversity and sentiment.
  • This method offers an advantage by not requiring user parameters during graph construction or word scoring.