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Multilayer network based comparative document analysis (MUNCoDA).

Viktor Sebestyén1, Endre Domokos2, János Abonyi1

  • 1University of Pannonia, MTA-PE "Lendület" Complex Systems Monitoring Research Group.

Methodsx
|May 20, 2020
PubMed
Summary
This summary is machine-generated.

This study introduces a multilayer network method (MUNCoDA) to identify commonalities in documents. It enables automated comparative analysis and topic clustering for better document understanding and summarization.

Keywords:
Document clusteringMulti-document summarizationNetwork similarityText-mining

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Area of Science:

  • Computational linguistics
  • Network science
  • Information retrieval

Background:

  • Comparative document analysis is crucial for understanding large text collections.
  • Existing methods may lack automated, network-based approaches for identifying textual commonalities.
  • Visualizing document structures aids in comparative evaluation.

Purpose of the Study:

  • To propose a novel multilayer network-based comparative document analysis (MUNCoDA) method.
  • To enable automated identification of common points and topic structures across multiple documents.
  • To facilitate multi-document summarization and topic importance analysis.

Main Methods:

  • Documents are transformed into networks of informative word-pairs.
  • A multilayer network is constructed to represent the collection of documents.
  • Network visualization, centrality measures, and similarity metrics are employed for analysis.
  • The method is automated using KNIME and MATLAB/Octave.

Main Results:

  • The MUNCoDA method successfully identifies commonalities and structures within document sets.
  • Document topics can be effectively clustered using developed similarity measures.
  • Network centralities allow for the assignment of topic importance values.
  • The approach supports automated multi-document summarization.

Conclusions:

  • The proposed MUNCoDA method offers an automated and effective approach for comparative document analysis.
  • Multilayer network analysis provides valuable insights into document structure and topic relationships.
  • This method enhances capabilities for information retrieval, summarization, and text mining.