Severity Classification Method for Traffic Accident Records Described in Short Sentences
ID:1739 View Protection:ATTENDEE Updated Time:2021-12-03 13:44:59 Hits:222 Poster Presentation

Start Time:Pending(Asia/Shanghai)

Duration:Pending

Session:No Session »

No files

Abstract
Aiming at the characteristics of urban accident report in developing country, the accident severity classification method based on semantic analysis model is proposed, and the process including taxonomy definition, text data preprocessing, word segmentation based on Hidden Markov Model (HMM), key word selection, weight setting and classifier construction based on decision tree. The purpose of the model is to lay a data foundation for evaluating the accident loss of descriptive traffic accident records in short sentences. This paper selects the traffic safety management data of Wujiang District of Suzhou City for sample analysis and verifies the accuracy of semantic analysis model by system-error evaluation.
Keywords
CICTP
Speaker
Ling Shen
Southeast University

Submission Author
Ling Shen Southeast University
Submit Comment
Verify Code Change Another
All Comments
Important Date
  • Conference Date

    Dec 17

    2021

    to

    Dec 20

    2021

  • Dec 16 2021

    Contribution Submission Deadline

  • Dec 24 2021

    Registration deadline

Sponsored By
Chinese Overseas Transportation Association
Chang'an University
Contact Information