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Updated: Sep 29, 2025

Cloud-Based Phrase Mining and Analysis of User-Defined Phrase-Category Association in Biomedical Publications
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POCASUM : Policy Categorizer and Summarizer Based on Text Mining and Machine Learning.

Rushikesh Deotale1, Shreyash Rawat1, V Vijayarajan1

  • 1School of Computer Science and Engineering, Vellore Institute of Technology, Vellore, India.

Soft Computing
|March 21, 2022
PubMed
Summary
This summary is machine-generated.

Users often skip privacy policies due to complex language. This study uses machine learning to categorize policy paragraphs, with artificial neural networks showing high accuracy in summarizing key information for better user understanding of data privacy.

Keywords:
Text classificationartificial neural networkmachine learningprivacy policytext miningtext summarization

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Area of Science:

  • Computer Science
  • Information Science

Background:

  • Users frequently disregard privacy policies because of their length and complex legal jargon.
  • This lack of engagement leaves users unaware of how their personal data is handled.
  • Incomplete or unclear policy statements from digital companies exacerbate the problem.

Purpose of the Study:

  • To develop a machine learning-based approach for summarizing and categorizing privacy policy information.
  • To enhance user comprehension of digital privacy policies by providing concise, categorized summaries.
  • To address the challenge of users not reading lengthy and obscure privacy policies.

Main Methods:

  • Proposed a machine learning-based policy categorizer to classify policy paragraphs.
  • Benchmarked various machine learning classifier models for performance evaluation.
  • Utilized a challenging dataset comprising textual privacy policies.

Main Results:

  • An artificial neural network model demonstrated superior accuracy in classifying policy paragraphs.
  • The machine learning approach effectively categorizes policy content under relevant attributes such as security and contact information.
  • The study successfully showed that machine learning can distill relevant information into brief summaries.

Conclusions:

  • Machine learning, particularly artificial neural networks, offers an effective solution for summarizing privacy policies.
  • This technology can significantly improve user awareness and control over personal data in the digital age.
  • Automated summarization of privacy policies enhances accessibility and user engagement with crucial data protection information.