| Title |
The Maintenance Factors of Apartment Building Defects Using Text Mining Techniques |
| Authors |
방홍순(Bang, Hong-Soon) ; 허한결(Heo, Han-Kyul) ; 김옥규(Kim, Ok-kyue) |
| DOI |
https://doi.org/10.5659/JAIK.2022.38.9.309 |
| Keywords |
Text Mining; An Apartment House; Defect; Secondary Defects; Analysis |
| Abstract |
There are secondary defects in apartment buildings that are not directly produced from construction errors, but are derived from other types
of defects. To improve the quality of the type of construction that causes these secondary defects, it is important to define and manage them
by analyzing data regarding defects in apartment buildings. This study analyzed approximately 1.33 million cases that finished defect repairs
in 2019 then defined the frequency and repair costs of fundamental and secondary defects. This analysis revealed that secondary defects had
accounted for 3.83% of the entire defect frequency and made up 6.08% of the repair costs. Using text mining techniques, this analysis
presented the types of construction that had caused secondary defects in apartment buildings in the order of frequency and average similarity
to reduce such secondary defects. According to the similarity analysis of the types of construction, wallpaper work topped the frequency
order with 68,060 cases, which took up 38.36%, and its similarity was 0.615 on average. Furthermore, with 4,518 cases, electricity work was
first in the average frequency at 2.54% and its average similarity was 0.955. To present these results as a whole, the word cloud technique
was used. |