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面向ATMS的道路安全信息清洗技术研究

Data Cleaning Technique of Road Safety Information Based on ATMS
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摘要 在ATMS中,信息是最核心的内容,系统的各项功能都是以信息的应用为中心展开的。为了在ATMS中保证使用数据的质量,提高信息资源的利用率,降低信息资源的周期损耗,提高系统的处理效率,减少系统的开销,采用数据清洗技术,建立了适合ATMS系统信息需求的数据清洗框架,实现对现有采集到的道路安全信息数据进行高效率的优化处理,使输入到ATMS系统的信息数据能保证系统做出高质量的决策,进而提高系统的运行效率。 In ATMS(Advanced Traffic Management System),information is the most core content.The various functions of the system are based on information in the application as the center spread.In order to guarantee the quality of the data used in ATMS,to improve the utilization of information resources but reduce the loss of information resources cycle,to improve the processing efficiency of the system but reduce the overhead of the system,this paper uses the data clean technology to establish a data clean framework,which has suited the ATMS's demand of the information data cleaning and realized the high-efficiency optimized processing of the road safety message data gathered currently.As a result,The data input into the ATMS can ensure the system make hign-quality decisions.Thus,the system's operating efficiency can be promoted.
作者 刘峰 成卫
出处 《交通信息与安全》 2012年第6期33-37,共5页 Journal of Transport Information and Safety
基金 昆明理工大学创新基金项目(批准号:2010YC131)资助
关键词 智能交通 ATMS 道路安全信息 数据清洗 intelligent transportation ATMS road safety information data cleaning
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  • 1王笑京,张可,张建通.ITS/TICS中央数据登记薄标准及其在交通共用信息平台建设中的应用[J].ITS通讯,2002(3). 被引量:1
  • 2Aebi, D., Perrochon, L. Towards improving data quality. In: Sarda, N.L., ed. Proceedings of the International Conference on Information Systems and Management of Data. Delhi, 1993. 273~281.
  • 3Wang, R.Y., Kon, H.B., Madnick, S.E. Data quality requirements analysis and modeling. In: Proceedings of the 9th International Conference on Data Engineering. Vienna: IEEE Computer Society, 1993. 670~677.
  • 4Rahm, E., Do, H.H. Data cleaning: problems and current approaches. IEEE Data Engineering Bulletin, 2000,23(4):3~13.
  • 5Galhardas, H., Florescu, D., Shasha, D., et al. AJAX: an extensible data cleaning tool. In: Chen, W.D., Naughton, J.F., Bernstein, P.A., eds. Proceedings of the 2000 ACM SIGMOD International Conference on Management of Data. Texas: ACM, 2000. 590.
  • 6Hernandez, M.A., Stolfo, S.J. Real-World data is dirty: data cleansing and the merge/purge problem. Data Mining and Knowledge Discovery, 1998,2(1):9~37.
  • 7Lee, M.L., Ling, T.W., Lu, H.J., et al. Cleansing data for mining and warehousing. In: Bench-Capon, T., Soda, G., Tjoa, A.M., eds. Database and Expert Systems Applications. Florence: Springer, 1999. 751~760.
  • 8Monge, A.E. Matching algorithm within a duplicate detection system. IEEE Data Engineering Bulletin, 2000,23(4):14~20.
  • 9Monge, A.E., Elkan, C. The field matching problem: algorithms and applications. In: Simoudis, E., Han, J.W., Fayyad, U., eds. Proceedings of the 2nd International Conference on Knowledge Discovery and Data Mining. Oregon: AAAI Press, 1996. 267~270.
  • 10Savasere, A., Omiecinski, E., Navathe, S.B. An efficient algorithm for mining association rules in large databases. In: Dayal, U., Gray, P., Nishio, S., eds. Proceedings of the 21st International Conference on Very Large Data Bases. Zurich: Morgan Kaufmann, 1995. 432~444.

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