Convolutional Neural Network Algorithm–Based Novel Automatic Text Classification Framework for Construction Accident Reports (Record no. 814982)

MARC details
000 -LEADER
fixed length control field 02891aab a2200241 4500
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fixed length control field 240216b20232023|||mr||| |||| 00| 0 eng d
022 ## - INTERNATIONAL STANDARD SERIAL NUMBER
International Standard Serial Number 0733-9364
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Luo, Xixi
9 (RLIN) 880920
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Li, Xinchun
9 (RLIN) 880921
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Song, Xuefeng
9 (RLIN) 880922
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Liu, Quanlong
9 (RLIN) 880923
245 ## - TITLE STATEMENT
Title Convolutional Neural Network Algorithm–Based Novel Automatic Text Classification Framework for Construction Accident Reports
300 ## - PHYSICAL DESCRIPTION
Extent 1-12 p.
520 ## - SUMMARY, ETC.
Summary, etc. Construction sites remain one of the most hazardous workplaces globally. To improve workplace safety in the construction industry and reduce the personal injuries and socioeconomic impacts resulting from workplace accidents, tacit knowledge containing fundamental causes of accidents or specific contextual factors can be extracted from past accident narrative reports. However, manually analyzing unstructured or semistructured textual data stored in records is a daunting task, and requires the use of automated and intelligent technologies to achieve rapid and accurate knowledge acquisition. Therefore, this paper proposes a text self-classification model based on deep learning natural language processing (NLP) technology for automated classification of construction site accident cases by accident type. First, combined with two statistical measures, mutual information and information entropy, the preprocessed text data were subjected to phrase segmentation to identify more complete and accurate accident precursor information without human intervention. Then a complete multilayer and multisize convolutional neural network (CNN) model was constructed using pretrained Word2Vec word embeddings for text self-classification tasks. Finally, the test results of the CNN classification algorithm were compared with the practical application results of three shallow learning algorithms, and the performance of different types of classification algorithms was evaluated. The results showed that the CNN-based deep learning algorithm developed in this paper demonstrated excellent feature extraction and learning abilities in the task of automatic text classification in the field of NLP. This not only demonstrated that reliable accident prevention knowledge could be obtained from the textual descriptions of construction accidents, but also provided a novel model reference for document archiving and information retrieval.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Deep Learning
9 (RLIN) 166900
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Natural Language Processing (NLP)
9 (RLIN) 880924
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Construction Safety
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Text Classification
9 (RLIN) 692730
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name entry element Accident Injury Types
9 (RLIN) 880925
773 0# - HOST ITEM ENTRY
Place, publisher, and date of publication Reston,Virginia, U.S.A : American Society of Civil Engineers/ American Concrete Institute
International Standard Serial Number 07339364
Title ASCE: Journal of Construction Engineering and Management
856 ## - ELECTRONIC LOCATION AND ACCESS
Uniform Resource Identifier <a href="https://doi.org/10.1061/JCEMD4.COENG-13523">https://doi.org/10.1061/JCEMD4.COENG-13523</a>
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Source of classification or shelving scheme Dewey Decimal Classification
Suppress in OPAC No
Koha item type Articles
-- 14993
-- Mr. Muhammad Rafique Al Haj Rajab Ali (Late)
Holdings
Not for loan Home library Serial Enumeration / chronology Total Checkouts Date last seen Koha item type
  Periodical Section Vol.149, No.12 (December 2023)   16/02/2024 Articles