{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,8,23]],"date-time":"2025-08-23T00:08:40Z","timestamp":1755907720988,"version":"3.44.0"},"publisher-location":"New York, NY, USA","reference-count":15,"publisher":"ACM","license":[{"start":{"date-parts":[[2023,11,18]],"date-time":"2023-11-18T00:00:00Z","timestamp":1700265600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.acm.org\/publications\/policies\/copyright_policy#Background"}],"content-domain":{"domain":["dl.acm.org"],"crossmark-restriction":true},"short-container-title":[],"published-print":{"date-parts":[[2023,11,18]]},"DOI":"10.1145\/3603273.3628763","type":"proceedings-article","created":{"date-parts":[[2024,1,9]],"date-time":"2024-01-09T18:12:40Z","timestamp":1704823960000},"page":"258-262","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Study of A Streamlining Method Based on Big Data"],"prefix":"10.1145","author":[{"ORCID":"https:\/\/orcid.org\/0009-0000-1922-8898","authenticated-orcid":false,"given":"Xin","family":"Yin","sequence":"first","affiliation":[{"name":"Hangzhou Institute of Applied Acoustics, China"}]}],"member":"320","published-online":{"date-parts":[[2024,1,9]]},"reference":[{"key":"e_1_3_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICCV.2015.123"},{"key":"e_1_3_2_1_2_1","volume-title":"Detecting online auction shilling frauds using supervised learning [J]. Expert Systems with Applications., 41(6):3027\u22123040","author":"Tsang Sidney","year":"2014","unstructured":"Sidney Tsang, Yun SingKoh, Gillian Dobbie, (2014) Detecting online auction shilling frauds using supervised learning [J]. Expert Systems with Applications., 41(6):3027\u22123040."},{"key":"e_1_3_2_1_3_1","volume-title":"ACOSampling: An ant colonyoptimization based undersampling method for classifying imbalanced DNA microarray data[J]. Neurocomputing., 101: 309\u2212318","author":"Yu Hualong","year":"2013","unstructured":"Hualong Yu, Jun Ni, Jing Zhao. (2013) ACOSampling: An ant colonyoptimization based undersampling method for classifying imbalanced DNA microarray data[J]. Neurocomputing., 101: 309\u2212318."},{"key":"e_1_3_2_1_4_1","volume-title":"Learning to improve medical decision making from imbalanced data without a priori cost[J].BMC Medical Informatics and Decision Making., 14: No.111","author":"Wan Xiang","year":"2014","unstructured":"Xiang Wan, Jiming Liu, William K Cheung, (2014) Learning to improve medical decision making from imbalanced data without a priori cost[J].BMC Medical Informatics and Decision Making., 14: No.111."},{"key":"e_1_3_2_1_5_1","volume-title":"Fitting and experimental validation of the viscosity model of modified PP materials based on LM-UGO algorithm with PVT model[J]., 46(12):37-42","author":"Mao Huajie","year":"2018","unstructured":"Huajie Mao, Bo He, Wei Guo, (2018) Fitting and experimental validation of the viscosity model of modified PP materials based on LM-UGO algorithm with PVT model[J]., 46(12):37-42."},{"issue":"5","key":"e_1_3_2_1_6_1","first-page":"27","article-title":"Preliminary study on spatialization of statistical data in village and town planning[J]","volume":"37","author":"Liu Xue","year":"2016","unstructured":"Xue Liu, Zhangxia Liu. (2016) Preliminary study on spatialization of statistical data in village and town planning[J]. Chinese Journal of Agricultural Resources and Regional Planning, 37(5):27-34.","journal-title":"Chinese Journal of Agricultural Resources and Regional Planning"},{"issue":"6","key":"e_1_3_2_1_7_1","first-page":"956","article-title":"Visual analysis of geospatial multi-dimensional data via a dynamic arrangement of parallel coordinates[J]","volume":"24","author":"Zhou Zhiguang","year":"2019","unstructured":"Zhiguang Zhou, Jiajun Yu, Zhiyong Guo, (2019) Visual analysis of geospatial multi-dimensional data via a dynamic arrangement of parallel coordinates[J]. Journal of Image and Graphics., 24(6):956-968.","journal-title":"Journal of Image and Graphics."},{"key":"e_1_3_2_1_8_1","doi-asserted-by":"publisher","DOI":"10.4028\/www.scientific.net\/AMM.336-338.2339"},{"key":"e_1_3_2_1_9_1","doi-asserted-by":"publisher","DOI":"10.4028\/www.scientific.net\/AMM.580-583.2860"},{"issue":"3","key":"e_1_3_2_1_10_1","first-page":"44","article-title":"Application of Elevation Anomaly Fitting Model in Bridge Cross-River Level Measurement[J]","volume":"12","author":"Xue Tao","year":"2015","unstructured":"Tao Xue, Hui Chen, ChengGao. (2015) Application of Elevation Anomaly Fitting Model in Bridge Cross-River Level Measurement[J]. Modern Transportation Technology, 12( 3): 44-46.","journal-title":"Modern Transportation Technology"},{"volume-title":"PRELIMINARY DRAFT [M]","author":"Manual Porter M","key":"e_1_3_2_1_11_1","unstructured":"Porter M B.(2011) The BELLHOP Manual and User's Guide: PRELIMINARY DRAFT [M]. La Jolla, CA, USA: Heat Light, and Sound Research, Inc. Press, USA."},{"key":"e_1_3_2_1_12_1","doi-asserted-by":"publisher","DOI":"10.4028\/www.scientific.net\/KEM.693.1391"},{"key":"e_1_3_2_1_13_1","volume-title":"Research on the Application of BP Neural Network Optimized by Genetic Algorithm in Lianyungang Port Throughput Prediction[D]","author":"Ke Yang","year":"2017","unstructured":"Yang Ke. (2017) Research on the Application of BP Neural Network Optimized by Genetic Algorithm in Lianyungang Port Throughput Prediction[D]. Shenzhen University."},{"key":"e_1_3_2_1_14_1","volume-title":"Research on the method of GPS elevation anomaly fitting based on artificial neural network[D]","author":"Cao Xiange","year":"2008","unstructured":"Xiange Cao. (2008) Research on the method of GPS elevation anomaly fitting based on artificial neural network[D].China University of Geosciences, Wuhan."},{"key":"e_1_3_2_1_15_1","unstructured":"Guangcheng Zhang.(2004) Practical Numerical Analysis [M]. Sichuan University Press Chengdu."}],"event":{"name":"AAIA 2023: 2023 International Conference on Advances in Artificial Intelligence and Applications","acronym":"AAIA 2023","location":"Wuhan China"},"container-title":["Proceedings of the 2023 International Conference on Advances in Artificial Intelligence and Applications"],"original-title":[],"link":[{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3603273.3628763","content-type":"unspecified","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/dl.acm.org\/doi\/pdf\/10.1145\/3603273.3628763","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,8,22]],"date-time":"2025-08-22T19:35:26Z","timestamp":1755891326000},"score":1,"resource":{"primary":{"URL":"https:\/\/dl.acm.org\/doi\/10.1145\/3603273.3628763"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2023,11,18]]},"references-count":15,"alternative-id":["10.1145\/3603273.3628763","10.1145\/3603273"],"URL":"https:\/\/doi.org\/10.1145\/3603273.3628763","relation":{},"subject":[],"published":{"date-parts":[[2023,11,18]]},"assertion":[{"value":"2024-01-09","order":3,"name":"published","label":"Published","group":{"name":"publication_history","label":"Publication History"}}]}}