數據清洗 的英文怎麼說

中文拼音 [shǔjùqīngxǐ]
數據清洗 英文
data cleaning
  • 數 : 數副詞（屢次） frequently; repeatedly
  • 據 : 據Ⅰ動詞1 （占據） occupy; seize 2 （憑借; 依靠） rely on; depend on Ⅱ介詞（按照; 依據） according...
  • 清 : Ⅰ形容詞1 （純凈） unmixed; clear 2 （寂靜） quiet 3 （清楚） distinct; clarified 4 （一點不留） w...
  • 洗 : 洗動詞1 （用水等去掉物體上的臟東西） wash; bathe 2 [宗教] （洗禮） baptize 3 （洗雪） redress; ri...
  • 數據 : data; record; information
  • 清洗 : 1. （洗干凈） wash; clean; rinse 2. （清除） purge; comb out; eliminate
  1. This article canvass the status quo of the archive ' s automatization administration and the develop status of data mining, and discusses how to combine the data mining technology with the archive work from data cleaning means, data mining arithmetic, and data storage etc. and this article put forword a data mining syst em design idea. this article ' s structure is : first, in allusion to the archive data status quo, the pretreatment work of archive data that include data quality evaluation, data cleaning and data commut - ation process is bringed forword ; second, in the process of realizating data mining, the article discusses conception description, association rule, class three familiar means of applicating data mining, also put inforword the concrete arithmetic and the program design chart, and discusses the range and the foreground of all kinds of arithmetic when they are applicated in the archive ; third, the base of so you say, this article also discusses the importance of the archice applicate data storage and the means of realizing it ; last, the article discusses seval important problem of realizing an archive data mining system from data, diversity, arithmetic multiformity, mining result variety and the data pretreatment visibility, mining object descriptive visibility, mining process visibility, mining result visibil ity, user demand description and problem defining etc aspect. the article ' s core is how to import data mining technology in the archive work

    本文評述了檔案自動化管理現狀和數據挖掘技術的發展狀況，從數據清洗方法、數據挖掘演算法、數據倉庫的建立等方面論述了如何將數據挖掘技術與檔案工作相結合的具體思路，並提出了一個數據挖掘系統的設計思想。文章首先，針對檔案數據的現狀，提出了應對檔案數據進行預處理工作，包括數據質量評估、數據清理、數據變換和歸約等過程；其次，在具體實現數據挖掘過程中，本文結合檔案數據的特點探討了概念描述、關聯規則、分類等三種常見挖掘形式的實現方法，提出了具體的實現演算法和程序設計框圖，並論述了各種演算法在檔案工作中的應用范圍及前景；第三，在上述基礎上，又論述數據倉庫在檔案數據挖掘中的重要性並提出了實現一個檔案數據倉庫的方法；最後，從處理數據的多樣性、演算法的多樣性、挖掘結果的多樣性、數據預處理可視化、挖掘對象描述的可視化、挖掘過程可視化、結果顯示可視化、用戶需求的描述及問題定義等幾方面討論了實現一個檔案數據挖掘系統的幾個重點問題。全文以探討如何將數據挖掘技術引入到具體的檔案工作實踐中為核心。
  2. This thesis includes four parts in which the technologies of web usage mininig are systematically researched. in the first part we summarize the techniques of data mining and web usage mining, present the significance of the research on web usage mininig, the status of research and the problem which web usage mininig will face with. in the second part we discuss the web usage mininig according to the process of web mining. in the stage of data preparing and preprocessing we discuss the algorithm of data cleaning, user and session identification in detail, and present a data model of association rules and sequential patterns in the stage of pattern discovery, discuss the useful method of pattern analysis in last stage. a synthesis clustering algorithm cppc is proposed in the third part of this thesis

    本文分主要從以下四個方面對web使用挖掘進行了系統的分析和研究。第一是對數據挖掘和web挖掘進行了概述，闡述了web挖掘的意義、研究的現狀、面臨的問題。第二是討論了web使用挖掘的三個階段：在數據準備和預處理階段重點討論了數據清洗及用戶和會話識別演算法；在模式發現階段定義了關聯規則和序列模式的數據模型；模式分析階段則討論了現行的幾種分析方法。
  3. Data migration centralizes the research of verifying, extracting, transforming and loading data

    數據遷移主要研究數據校驗、數據清洗、數據轉換和數據加載等方面的問題。
  4. And the principle and the method of data migration with data cleaning function are studied and applied in the management information system

    然後，介紹了數據清洗原理和數據遷移方法，並研究了具有數據清洗功能的數據遷移技術。
  5. Data cleaning based on fuzzy match

    基於模糊匹配的數據清洗
  6. As one of the most advanced research problems in data warehouse system, data lineage tracing may play an important role in the area of in - depth data analysis, and help us to validate the source data, cleaning rules and transformation rules, and thus improving the quality of data warehouse

    數據志跟蹤技術是數據倉庫研究中一個最新的前沿性課題，不僅可以支持更全面、更深入的數據分析，還可以幫助技術人員驗證源數據、清洗規則和轉換處理的正確性，從而提高數據倉庫的質量。
  7. 3 the concept of equivalence matrix, which expresses equivalence relation in rough set information system, is introduced ; the relations between equivalence matrix and equivalence classes are discussed. the algorithms for data cleaning and rules extraction in knowledge system based on matrix computation are proposed and their complexity of computation is analyzed

    3 、在等價矩陣概念的基礎上，分析了粗糙集知識系統中等價劃分與等價摘要矩陣的關系，採用等價矩陣來表示粗糙集的等價關系，提出了一種對數據庫知識系統進行數據清洗以及從中提取決策規則的矩陣演算法，分析了該演算法的計算復雜性。
  8. This paper describes the basic features and components of data warehouse system, and deals how to use description - driven technology to integrate different data warehouse systems, how to implement the change from one data schema to another, how to clean dirty data in data transformation process, and how to exchange data among different components or systems. at last, this paper takes two products to illustrate how to implement systems following these principles and methods. these two products are the e - chain system as an application in commerce domain, and the ftedws system as an application in engineer test domain

    本文分析了數據倉庫系統軟體的基本特徵，提出了利用描述驅動技術來實現數據倉庫系統的集成管理，描述了etl操作和分析處理的基本處理流程和相應的執行構件，定義了集成框架中數據模式轉換規則和數掘清洗規則，構建了一個基於星型模式和對象模型的分析模型和相應的數據查詢語言，提出了集成框架系統構件間的數據交換標準，並定義了基於此標準的的數據交換和元數據交換方法，探討了集成框架標準構件管理的基本方法和權限管理，最後介紹了數據倉庫集成框架系統在商業領域的應用實例e - chain系統和工程試驗領域的應用實例ftedws系統。
  9. Then the thesis further analyses some core techniques including the system of database, data warehouse and data mining and so on, and presents the frame of function of bank crm. the thesis puts its emphasis on the research on the data preprocessing of data warehouse, data copying, data cleansing, data integration and quality verifying included. finally the thesis discusses the key technology of data warehouse in bank crm - the cleansing of data of customers, and presents some methods of cleansing aiming at noisy values, missing values, conflicting values and duplicated values

    本文在充分分析銀行crm的需求的基礎上，提出了基於數據倉庫的銀行crm系統的體系結構，並進一步分析了該體系結構中客戶數據庫系統、數據倉庫、數據挖掘等核心技術組件的內涵，給出了銀行crm系統的功能構架；重點研究了銀行業務系統多年積累的客戶數據向數據倉庫遷移的預處理方法和過程，其過程包括數據復制、數據清洗轉換、數據集成、質量檢驗和數據裝載；最後討論了銀行crm系統應用數據倉庫的關鍵技術：客戶數據清洗，給出了針對噪聲數據、空缺數據、不一致數據和重復數據的清洗方法。
  10. On the basis of analyzing current problems existing in data cleaning, especially after abundant researching on exploring and eliminating approximately duplicated records, this paper brings forward record matching method and eliminating approximately duplicated records method based on rdbms, expecting to eliminate approximately duplicated records in data warehouse

    本文在對當前的數據清洗問題，特別是探測和消除重復記錄方面，做了充分的研究后，提出了基於rdbms的記錄匹配方法和消除數據倉庫中相似重復記錄的方法，以期消除數據倉庫中的相似重復記錄。
  11. This essay first dicussed the key steps of preprocessing in web log mining, which include data abstract, data cleaning, user and session identification and path completion etc. especialy we proposed the algorithm of the web log data preprocessing include frame page. and secondly we discussed the technology of building an adaptive web site, include log data cluster mining, user visiting pattern learning, site structure transformation and presentation etc. ; and we proposed indual user log visiting pattern, user model onling learning algorithm, index pages synthesising algorithm, site structure transformation and presentation algorithm and so on

    本論文首先討論了web日誌挖掘預處理中的各步驟：數據抽象、數據清洗、用戶與會話識別、訪問路徑補全，給出了每一步驟的演算法實現；並特別討論了含有frame頁的日誌數據預處理過濾演算法。其次討論了構建自適應站點技術，包括日誌數據聚類挖掘、用戶訪問模式學習、站點結構轉化與呈現等；提出了單用戶日誌訪問模型，給出了用戶模型在線學習演算法、索引頁面綜合演算法、站點結構轉化及呈現演算法等。
  12. Through the analysis on the reasons based on extension theory, the paper has established a new method called data mining consulting to solve the data quality problem by metasynthesis method including software designing, management and data mining testing, etc

    本文以可拓學方法，通過系統分析產生臟數據的原因，提出了基於學科鏈方法的數據清洗方案。
  13. To solve some existed problems in data mining, the thesis gives out a few resolutions with the new mathematical tool. information theory and multiple statistics are introduced into rough analysis together with rough set theory and other techniques, new results are giving for knowledge discovering, associative rules mining, pattern classification and data cleaning, etc. after a brief summary on data mining and rough set theory, the research works in the thesis can be descript as follows : 1

    Rough集理論是一種新型的處理不確定性知識的數學工具，圍繞著數據挖掘領域存在的問題，本文利用rough集理論與rough分析工具，提出若干解決方案，同時在具體處理問題過程中引入了信息理論、因子分析等方法，與rough分析結合使用，討論了rough集技術在知識發現、關聯規則挖掘、模式分類以及數據清洗等問題中的應用。
  14. He obeyed and followed the instructions of his supervisors in his assignments and was willing to perform duties not relating to estate management work, for instance, measuring and recording weather data, cleaning the utensils like evaporation pan, rain gauge etc. he set high standards for himself

    在其他工作上，能夠嚴格遵從上司的指示完成任務。此外，他樂于接受保安以外的工作，如協助量度及記錄天氣數據，清洗蒸發皿雨量器等器具，而且做得一絲不茍。
  15. Examining and eliminating approximately duplicated records is one of main problems needed solve for data cleaning and improving data quality

    檢測和消除相似重復記錄是數據清洗和提高數據質量要解決的主要問題之一。
  16. Abstract examining and eliminating approximately duplicated records is one of main problems needed to solve for data cleaning and improving data quality

    摘要檢測和消除數據倉庫中的相似重復記錄是數據清洗和提高數據質量要解決的主要問題之一。
  17. The paper systematically discussed design and implement steps on multi - dimensions data model, the interlink between data warehouse and multi - sources, the capture of changed data, the increased - load of dimension table and the data cleaning by specific examples

    系統的分析並舉例說明了多維數據模型設計，數據倉庫與多數據源互聯，變化數據捕捉，維表增量加載，數據清洗等技術要點的設計與具體實現步驟。
  18. However, data cleaning is a significant method to improve data quality

    數據清洗是提高數據質量的重要途徑。
  19. On the other hand, most information systems are base on distributed database, and they evolved to current style after many times of discrete development

    從多個異構數據源獲取業務數據，進行數據清洗和轉換后，存儲到數據倉庫的過程，稱為etl （ dataextraction ， transformation ， loading ）過程。
  20. The objective of data cleaning is to solve data quality issue due to the reason hereinbefore. thus data cleaning is regarded as one of the most important prolems for creating data warehouse

    數據清洗的目的就是要解決由上述原因產生的數據質量問題，因此數據清洗被認為是建立數據倉庫所要解決的最重要的問題之一。
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