@article{ref1,
title="Data mining method of road traffic accidents based on feature weighting",
journal="Advances in transportation studies",
year="2022",
author="Fu, X. and Li, Q. and Wang, L. T. and Wang, D. G. and Liu, X. L.",
volume="",
number="SI 4",
pages="103-112",
abstract="In order to realize high precision and high efficiency mining of road traffic accident data, this paper proposes a new method of road traffic accident data mining based on feature weighting. Firstly, according to the principle of association rules, support, confidence and similarity are calculated to complete the collection of traffic data. Secondly, the collected traffic data is sparsely represented, TF-IDF feature weighting method is used to calculate the sample data, extract the features of traffic accident data and complete the weighting process. Finally, by calculating the dissimilarity of traffic accident data, the traffic accident data mining function is constructed to complete the traffic accident data mining. The experimental results show that the proposed method can improve the accuracy of traffic accident data mining, with the highest accuracy of 99%, and shorten the time of mining, with the maximum time of less than 2 minutes.<p /> <p>Language: en</p>",
language="en",
issn="1824-5463",
doi="",
url="http://dx.doi.org/"
}