智能數據挖掘 的英文怎麼說

中文拼音 [zhìnéngshǔjùwājué]
智能數據挖掘 英文
intelligent data mining
  • 智 : Ⅰ名詞1 （智慧; 見識） wisdom; intelligence; knowledge 2 （姓氏） a surname Ⅱ形容詞（有智慧; 聰明...
  • 能 : 能名詞（姓氏） a surname
  • 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...
  • 挖 : 動詞（用工具或手從物體的表面向里掘取） dig; excavate; scoop
  • 掘 : 動詞（刨; 挖） dig
  • 智能 : intellect; intelligence; mind; brain power; intellectuality; mentality; noopsyche; brow智能測試 i...
  • 數據 : data; record; information
  • 挖掘 : excavate; unearth; dig; tap; grub; hoe; grave
  1. At first, it will discuss the conditions and trend of current network optimization technology and pay much attention to the call quality test, then discuss the data mining algorithms and practical application forms, finally, integrated the algorithms and application forms, discussed how to apply data mining technology to network optimization and the steps to apply data mining in network optimization call quality test system base on the requirement of customer and pay much attention to the function of data mining technology in the system, the design detail of the data mining algorithms and the application result

    文中首先討論網路優化的現狀和發展並重點討論網路優化cqt測試的方法和流程，然後討論數據挖掘的各演算法和實際應用形式，最後將兩者結合，研究如何將數據挖掘應用到網路優化中，並根據客戶對網路優化cqt系統智能化的需求，討論具有數據挖掘功能的網路優化cqt系統的需求、設計和具體實現。在整個cqt系統的討論中，重點討論數據挖掘在cqt系統中的作用、具體演算法設計和應用結果。
  2. This paper recurred to the basic theory of rough set of data mining and under the direction of the frame of intelligent decision, the main theories include i ) the different methods of data mining on the base of rough set are used to deal with typical decision system namely consistent decision system and inconsistent decision system in order to carry through data reduction and rule distilment ; ii ) in the environment of dynamic increment database, the methods of data reduction to deal with the original data and increment data are discussed in the consistent and inconsistent decision system ; iii ) the method of data mining of rough set is analysized to treat with the attributes with priority ; iv ) on the base of basic rough set theory, the data analysis methods of amalgamation of rough set theory ; v ) and also the pre - disposal method to database is analysize

    本文從系統工程進行決策分析的角度出發，藉助數據挖掘技術中粗糙集的基本理論，在智能決策框架的指導下，研究了基於數據挖掘的智能決策理論及方法。主要理論包括：如何利用粗糙集對典型的決策系統即相容性決策系統和不相容性決策系統運用不同的數據挖掘方法進行有效的數據約減和規則提取；在增量動態的數據庫環境下討論了在典型決策系統中對原始數據和增量數據進行數據約減的方法；分析了帶有優先權屬性的粗糙集數據挖掘方法；以基本粗糙集為基礎探討了粗糙集擴展模型的數據分析方法；研究了粗糙集數據預處理方法。
  3. Data mining which is a full - scale intellectualized solution, makes enterprises apperceive the thing hypostases deeply, provides support for decision - making, and affords the customer intelligence service of deep levels more effective market activities, wins the higher income for enterprise

    數據挖掘是一個全面的智能化解決方案，使企業深入洞察事務的本質，並為決策提供支持，提供深層次的客戶智能服務、更有效的市場活動，為企業贏得更高收入。
  4. Specialized data mining tools containing intelligent agents are used to perform these tasks

    專業的數據挖掘功能包括用來實施該任務的智能代理。
  5. The third part talks about the analysis and design of the business intelligence module which is a part of zhen xiang project, then explores the application of data mining to provide market basket analysis, customer classification analysis and other intelligent analyses. we research on how to provide intelligent analysis based on data mining for the enterprise in the e - commerce system

    本文對振湘項目二期工程的商業智能分析子系統進行了分析和設計，嘗試應用數據挖掘來完成購物籃分析、客戶細分等分析功能，並且對在電子商務系統中結合企業需求提供基於數據挖掘的智能分析服務進行了有意義的研究探索。
  6. Therefore, the author established a intellectualized exhumation system basing on classification id3 decision - making tree arithmetic, and provided a valuable example for developing other data exhumation applying system

    因此，基於分類id3決策樹演算法，作者建立了一個智能挖掘體系，並為開發其它數據挖掘應用系統提供了一個有價值的實例。
  7. Learn more about db2 business intelligence software that helps you build an " information on demand " environment, combining data mining and multi - dimensional data access with advanced statistical and analytical functions in a real - time integrated environment. developerworks information management zone

    ：學習關于db2商業智能軟體的更多信息，可以幫助建立「隨需應變的」信息環境，在實時集成環境中將數據挖掘和多維數據訪問與高級統計和分析函數結合起來。
  8. An overview on intelligentized data mining

    智能化數據挖掘方法綜述
  9. 3. data exhumation means in higher school intellectualized educational administration system the author provided decision - making analysis thought for educational administration work by using choosing - course and application - course models to recognize, analyze and forecast the behavior of students and teachers

    高校智能教務系統中的數據挖掘手段針對教務系統中選課、課程申請模塊對學生、教師的行為進行識別、分析和預測，為教務工作提供決策分析思路。
  10. The core of this thesis is represented with hereinafter items : on the base of studying many information exhumation techniques and through collecting and analyzing the data of each tache, the author put forward a design thought which combines data exhumation and build technology of j2ee, and developed an intellectualized educational administration system that is suit for the situation of our country

    本次碩士論文設計的重點是在研究多種信息挖掘技術方法的基礎上，通過對教務信息管理全過程各個環節的數據進行採集與分析，提出了結合數據挖掘和j2ee架構技術結合的設計思路，開發出適合我國國情的智能教務系統。
  11. Web mining is one of hotspot of data mining technology in artificial intelligence fields, which implements some function as web access mode, web structure and rule, dynamic search for web content, is a more defiant subject

    Web挖掘為人工智慧領域中數據挖掘技術的一個熱點，它實現對web存取模式、 web結構和規則，以及動態的web內容的查找功能，是一個更具挑戰性的課題。
  12. Web mining is one of hotspot of data mining technology applied in artificial intelligence field. it is a more defiant subject that implements some function as discovering web access mode, web structure and rule and dynamic search for web content

    Web挖掘為人工智慧領域中數據挖掘技術的一個熱點，它實現對web存取模式、 web結構和規則，以及動態的web內容的查找功能，是一個更具挑戰性的課題。
  13. Based on integration of " high yield & benefit and good grain quality of modeled cultivation of foodstuff crop ( rice ) and its consultation system ", this thesis sets it ultimate goal to deal with the knowledge discovery in the consultation system of simulation - optimization decision making in quality and high - yielding rice cultivation. after a close study of the features of the database in rice cultivation, this thesis introduces the system engineering theory of agent aralysing and designing and offers a practical new way to promote the intelligence of the knowledge discovery system in rice cultivation database, to improve the efficiency of data mining and the human - computer interactive ability to realize the integrated knowledge - based combination between human and computer or among the sub - systems

    本文以廣西「糧食作物（水稻）兩高一優模式栽培技術集成與咨詢系統研究」為背景，以基於專家系統（ es ）的水稻優質高產栽培模擬優化決策咨詢系統的知識獲取問題為導向，針對水稻栽培數據庫的特點，從系統工程角度引入面向agent的分析與設計思想，提出一種用多agent從水稻栽培數據庫中發現知識的人機合作、半自動的知識獲取方法，實現利用多agent的自主性、反應性和社會性，提高水稻栽培數據庫知識發現系統的智能水平、數據挖掘效率和人機交互能力，實現人機之間、各子系統之間基於知識的柔性綜合集成，為水稻栽培知識發現提供了一條新的可行途徑。
  14. We can build data - base according to the datum of the higher school educational administration system. the data - base can tail after the module of course - choice for students, the module of course - application for teachers, the module of examining and approving flows and achievement - managing module to complete the distributed disposal of each flow on web

    已完成的教務系統可以提供智能化的挖掘分析功能，根據高校教務系統的基本數據，構建數據倉庫，對學生選課、教師申請課程、審批流程、成績管理等模塊的狀態進行跟蹤，完成web上各個流程的分佈處理。
  15. Intelligent question answering system based on data mining

    基於數據挖掘的智能答疑係統
  16. How can we explore the knowledge in the vast dataset, it become a arduous task facing the expert of crossing fields. and with the increasing of computing capacity, the maturity of ai algrithm and vast capacity of storage, datamining has unveiling itself and do well in some fields

    伴隨計算能力的增長，智能演算法的成熟及大規模數據存儲技術的成熟，作為自動發現知識的工具，數據挖掘（ dataming ）逐漸走出實驗室，進入生產領域並發揮了積極的作用。
  17. The paper describes the environment of business intelligence in crm in details. we analyze the technique and the process of data warehouse ( dw ) particularly. after studying the process of data mining ( dm ) deeply, we give a model of life cycle which is made up of six phases and four levels

    本文詳細描述了客戶關系管理中的商業智能環境，具體分析了數據倉庫技術及其建造過程的各個階段，深入研究了數據挖掘過程，提出了數據挖掘項目的生命周期法，將數據挖掘項目分為六個階段和四個層次。
  18. Research on knowledge acquisition over internet. integrated by newly achievements of intelligent search and data mining, we build the technique system of acquiring the design information and abstracting design knowledge, as well as the mechanism of self - study and self - update. 2

    對網路環境下的知識獲取進行了研究，結合智能搜索技術和數據挖掘技術的最新成果，建立了web環境下獲取設計素材和提煉設計知識的方法體系，以及與此相關的知識的自豐富、自更新機制。
  19. This thesis is focused on the study of data - mining technique in the intelligent decision - making auxiliary system. a data - mining system based on the in - situ investigating information and the in - situ analyzing and testing data is designed and realized. in order to manage the system and select the proper algorithm, an illustration table of the algorithm and a rule - selecting database of the algorithm are proposed in the model management of this system

    本文重點研究了智能輔助決策系統中的數據挖掘技術，設計並實現了現場調查信息和分析測試信息下的數據挖掘系統，在該系統的模型管理中，提出了演算法說明表和演算法選擇規則庫，用於演算法的管理和選擇。
  20. Data mining is defined as the nontrivial extraction of implicit, previously unknown, and potentially useful information from data or known as knowledge - discovery in databases ( kdd ). to do this, data mining uses computational techniques from statistics, machine learning and pattern recognition such as discriminate analysis, regression method, mathematical programming, decision tree, k - nearest neighbor, artificial neural network etc. although many positive attempts are done, the development and application of personal credit assessment model in chinese bank industry is still in its infancy

    數據挖掘是20世紀90年代後期人工智慧和數據庫領域興起的一種數據處理和知識發現（ kdd ）理論，是從大量的、不完全的、有噪聲的、模糊的和隨機的實際應用數據中，提取隱含在其中的信息和知識的過程。對數據進行分類和預測是數據挖掘的主要功能。數據挖掘用於信用評估的優勢主要在於: （ 1 ）能處理和修正實際數據問題，演算法模型具有自檢
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