Exploring Traffic Crash Narratives in Jordan Using Text Mining Analytics-Reference-Cited by-同舟云学术

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Exploring Traffic Crash Narratives in Jordan Using Text Mining Analytics

Published:2024-04-13 Issue: Volume: Page:
ISSN:
Container-title:2024 IEEE 3rd International Conference on Computing and Machine Intelligence (ICMI)
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Author:

Jaradat Shadi¹,Alhadidi Taqwa I.²,Ashqar Huthaifa I.³^ORCID,Hossain Ahmed⁴,Elhenawy Mohammed¹

Affiliation:

1. CARRS-Q Queensland University of Technology,Brisbane,Australia

2. Al-Ahliyya Amman University,Civil Engineering Department,Amman,Jordan

3. Arab American University,Civil Engineering Department,Palestine

4. University of Louisiana at Lafayette,Department of Civil Engineering,Lafayette,Louisiana

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10585267/10585616/10586010.pdf?arnumber=10586010

Reference24 articles.

1. Classifying Pedestrian Maneuver Types Using the Advanced Language Model

2. Natural Language Processing Based Method for Clustering and Analysis of Aviation Safety Narratives

3. Applying Few-Shot Learning in Classifying Pedestrian Crash Typing

4. Automated content analysis for construction safety: A natural language processing system to extract precursors and outcomes from unstructured injury reports

5. Driving behavior classification at signalized intersections using vehicle kinematics: Application of unsupervised machine learning

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Multitask Learning for Crash Analysis: A Fine-Tuned LLM Framework Using Twitter Data;Smart Cities;2024-09-01

2. Visual Reasoning and Multi-Agent Approach in Multimodal Large Language Models (MLLMs): Solving TSP and mTSP Combinatorial Challenges;Machine Learning and Knowledge Extraction;2024-08-13

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