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A Hybrid Systematic Literature Review and Automated Content Analysis for Named Entity Recognition in Disaster Information Management

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The research aims to evaluate the use of named entity recognition in disaster information management by examining existing literature and methodologies.
Conducted a systematic literature review to identify trends and methodologies in NER for disasters.
Utilized automated content analysis to assess the application of NER in different contexts.
Analyzed challenges faced by traditional NER methods and explored machine learning and deep learning solutions.
Identified critical challenges in NER applications, including adaptability and handling diverse text sources.
Highlighted key datasets and feature extraction techniques relevant for NER in disaster scenarios.
Proposed actionable insights for enhancing NER solutions, focusing on improving accuracy and efficiency in disaster response.

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Hybrid approach analyzes named entity recognition in disaster management, suggesting improvements for information extraction.

Shidik et al. (2026) studied this question.

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