{"title":"使用关键字组从施工钻孔记录中自动提取岩土工程信息","authors":"Byeong-Soo Yoo, Jin-Tae Han, Eomzi Yang","doi":"10.1007/s12205-024-0605-7","DOIUrl":null,"url":null,"abstract":"<p>Geotechnical survey data is essential for the construction of civil engineering and architectural structures, with high utilization rates. However, variations in the forms used across different entities such as host organizations, contractors, and structures necessitate manual input tasks during the database creation process, leading to significant consumption of human and time resources. To address this challenge, both standard and distributed boring logs were collected and subjected to comprehensive feature analysis. Based on this analysis, an algorithm capable of automatically extracting the desired geotechnical information from boring logs was developed. This algorithm is versatile, applicable across various formats, and has demonstrated a staggering improvement in information processing speed compared to manual input.</p>","PeriodicalId":17897,"journal":{"name":"KSCE Journal of Civil Engineering","volume":"58 1","pages":""},"PeriodicalIF":1.9000,"publicationDate":"2024-08-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Automated Geotechnical Information Extraction from Construction Boring Logs Using Keyword Groups\",\"authors\":\"Byeong-Soo Yoo, Jin-Tae Han, Eomzi Yang\",\"doi\":\"10.1007/s12205-024-0605-7\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Geotechnical survey data is essential for the construction of civil engineering and architectural structures, with high utilization rates. However, variations in the forms used across different entities such as host organizations, contractors, and structures necessitate manual input tasks during the database creation process, leading to significant consumption of human and time resources. To address this challenge, both standard and distributed boring logs were collected and subjected to comprehensive feature analysis. Based on this analysis, an algorithm capable of automatically extracting the desired geotechnical information from boring logs was developed. This algorithm is versatile, applicable across various formats, and has demonstrated a staggering improvement in information processing speed compared to manual input.</p>\",\"PeriodicalId\":17897,\"journal\":{\"name\":\"KSCE Journal of Civil Engineering\",\"volume\":\"58 1\",\"pages\":\"\"},\"PeriodicalIF\":1.9000,\"publicationDate\":\"2024-08-07\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"KSCE Journal of Civil Engineering\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1007/s12205-024-0605-7\",\"RegionNum\":4,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"ENGINEERING, CIVIL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"KSCE Journal of Civil Engineering","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1007/s12205-024-0605-7","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, CIVIL","Score":null,"Total":0}
Automated Geotechnical Information Extraction from Construction Boring Logs Using Keyword Groups
Geotechnical survey data is essential for the construction of civil engineering and architectural structures, with high utilization rates. However, variations in the forms used across different entities such as host organizations, contractors, and structures necessitate manual input tasks during the database creation process, leading to significant consumption of human and time resources. To address this challenge, both standard and distributed boring logs were collected and subjected to comprehensive feature analysis. Based on this analysis, an algorithm capable of automatically extracting the desired geotechnical information from boring logs was developed. This algorithm is versatile, applicable across various formats, and has demonstrated a staggering improvement in information processing speed compared to manual input.
期刊介绍:
The KSCE Journal of Civil Engineering is a technical bimonthly journal of the Korean Society of Civil Engineers. The journal reports original study results (both academic and practical) on past practices and present information in all civil engineering fields.
The journal publishes original papers within the broad field of civil engineering, which includes, but are not limited to, the following: coastal and harbor engineering, construction management, environmental engineering, geotechnical engineering, highway engineering, hydraulic engineering, information technology, nuclear power engineering, railroad engineering, structural engineering, surveying and geo-spatial engineering, transportation engineering, tunnel engineering, and water resources and hydrologic engineering