數據採掘 的英文怎麼說

中文拼音 [shǔjùcǎijué]
數據採掘 英文
data excavating
  • 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...
  • 掘 : 動詞（刨; 挖） dig
  • 數據 : data; record; information
  1. The ids of the paper is network - based anomaly detection system. with the help of data mining technology, we bring forward a measure to describe the normal state of the network traffic and user behavior and extracting the useful rule from large network data. so we can establish the knowledge warehouse which describe the normal state of the network traffic and user behavior. the knowledge warehouse can be the standard in order to judge the normal state. we can find the dubitable connections according to account the state and anomly instances of connections

    論文在描述網路應用和用戶行為時採用數據挖掘技術從海量的網路數據中提取有用的規則，構建了一個描述正常狀態下的網路應用和用戶行為的規則集，這個規則集是用來判斷網路應用和用戶行為是否正常的標準，論文根據這個標準分析當前網路連接的異常情況，將可疑的連接找出來。
  2. In this paper, we study focus on building intrusion detection model based the technique of data mining ( dm ). firstly, the paper designed a scheme to modeling intrusion detection based dm and bright forward the idea of descriptive model and classified model to intrusion detection. secondly, we designed and implemented a net data collection system with high performance and a scheme to pretreat net data. thirdly, after studying the algorithms to mine association rule and sequence rule in net data, we extended and improved the algorithms according to the characteristic of net data and the field knowledge of intrusion detection

    首先設計了基於數據挖掘技術的入侵檢測建模方案，提出使用該技術建立入侵檢測描述性模型和分類模型的思想，並用分類判決樹建立了入侵檢測分類模型；其次，設計和實現了一個高性能的網路數據採集系統和網路數據預處理的方案；然後，在對關聯規則挖掘和序列規則挖掘演算法進行研究的基礎上，結合網路數據的特性和入侵檢測領域的知識對演算法進行了擴展和改進，挖掘出了網路數據的關聯模式和序列模式；最後，研究了描述性模式的應用，並設計出基於模式匹配的入侵檢測引擎，該引擎具有誤用檢測和異常檢測功能。
  3. After analyzing the character of risk, i introduce data mining method into risk management, to solve the contradiction between great capacity of data and lack of information, the methods include mathematics statistics and artificial neural network ( ann ). then, i study on the methods of risk management in risk identification, risk evaluation and risk disposal, what is advanced, fault tree analysis method based on fuzzy probability, stochastic simulation method and the topsis method based on interval number all consider the characteristic of risk. finally, i discussed the application of information system ( mis ) in project risk management, and developed a risk management information system

    論文在深入分析了風險特徵之後，將數據挖掘技術引入風險管理，用以解決海量數據與貧乏信息之間的矛盾，所採用的技術有數理統計和人工神經網路（ ann ）兩種方法；接著，論文對風險識別、風險評價、風險處理中的風險管理方法進行了研究，所提出的基於模糊概率的故障樹技術、隨機模擬技術和基於區間數的topsis方法都體現了風險管理的特點；最後，論文對信息系統（ mis ）在工程項目風險管理中的應用進行了探討，開發出一個風險管理信息系統。
  4. Upon this foundation, a corpus - based algorithm was designed and implemented to acquire and filter binary semantic pattern rules automatically. in the algorithm, a data mining method for cross - level association rules is adopted, which is guided by metarule, to find the semantic laws of word combinations in chinese phrase corpus. then statistic results are used to filter the findings

    在此基礎上，本文設計並實現了基於語料庫的二元語義模式規則自動挖掘和優選演算法，該演算法先採用數據挖掘中元規則制導的交叉層關聯規則挖掘方法，自動發現漢語短語熟語料庫中詞語兩兩組合的語義規律，再根據統計結果自動優選后轉換生成候選二元語義模式規則集。
  5. During this period, area selecting, sampling, interviewer training, pilot testing and questionnaire revising were took action to ensure the quality of the research. then the author established the database on the requirements of hml and used it to analysis the shanghai household " s apparel consumption decision - making behavior and its influencing factors

    期間先後進行選取調查地區、調查對象及進行調研員的培訓等工作，同時對調查問卷也做了設計修改，採用入戶跟蹤問卷調查的方法，得出有效數據，建立基於hml數據挖掘技術要求的數據庫，並運用hml數據挖掘軟體系統分析了上海家庭服裝消費的決策行為及其影響因素。
  6. 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。
  7. Comparing with non - bnyain methods, it ' s prominent featares lay in that it combines the prior and posterior information, which avoids the disadvantag of subjective bias caused by simply using the prior information only, of blind search caused by the incomplete sample information, of noise affection caused by simply using the sample information only if we choice a suitable priof, we can conduct the bayesian leaming effectively, so it fits the problems of data mining and machine leaming that possess charaters of probability and statistics, especially when the samples are rare

    與非貝葉揚方法相比，貝葉斯方法的特出特點是其學習機制可以綜合先驗信息和后驗信息，既可避免只使用先驗信息可能帶來的主觀偏見，和缺乏樣本信息時的大量盲目搜索與計算，也可避免只使用樣本信息帶來的噪音的影響只要合理地確定先驗，就可以進行有效的學習。因此，適用於具有概率統計特徵的數據採掘和機器學習（或發現）問題，尤其是樣本難得的問題
  8. Firstly it uses data mining and statistic algorithms to detect dos attacks, and then determines the feature of attack flows, lastly uses various defense methods to weaken or eliminate the effect of attacks. the system ensures that when the network or victim systems are being attacked, they can continue to serve legitimate users

    它利用數據挖掘和統計演算法等檢測技術檢測dos攻擊，確定攻擊流量的特徵，並採取多種防禦措施來削弱和消除攻擊流量對網路和系統的影響，確保在攻擊發生的情況下，仍能為合法用戶提供服務。
  9. Finally, the paper give information of some critical module of this software. this software is customized for guizhou province aluminum company

    該系統利用聚類分析數據挖掘手段，分析出陰、陽極多個物理位置不同的採集點之間存在的邏輯位置組合。
  10. We came up with algorithm descriptions and reinforced our conclusion by means of real testing examples. some data mining techniques, which can be applied to semantic web mining, were also discussed in this thesis. we explored the suitability of inductive logic programming ( ilp ) method in semantic web mining in more detail, and showed how to make use of this method in the semantic context

    對于語義web挖掘中適合的數據挖掘技術進行了探討，提出了可採用歸納邏輯程序設計作為適合語義化web的數據挖掘技術，給出了如何應用這種技術的演算法描述，並通過具體實例驗證了這種方法對于語義化web環境下進行數據挖掘是可行性。
  11. According to the standard of kddcup ' 99 and by adopting numeric mixed coding, 41 features of the captured network packets are extracted and transferred into numerical form which can be accepted by neural network in this paper, we present a misuse detection model based on hybrid neural network and decision tree

    根據第三屆國際知識發現和數據挖掘競賽（ kddcup ' 99 ）標準，對截獲的網路數據包進行41維特徵抽取，並採用混合數值編碼方法，使這些特徵轉化為能被神經網路處理的數值形式。
  12. Data query and analysis focuses on on line analytical processing ( olap ) and data mining ( dm )

    數據查詢分析則主要採用聯機分析處理（ olap ）和數據挖掘的方法。
  13. This paper will discuss the background, requirement and significance of the study firstly. after that we will compare the present relative technologies and discuss the feasibility of using data mining and crm in campus information system

    本文首先討論了該課題的背景、需求及其研究意義，然後比較了國內外現有的技術和應用，探討在校園信息系統中採用crm理念和數據挖掘技術的可行性。
  14. The fundamental theoretical framework of this dissertation is the " stimulus - response " model of psychological behaviorism. the author applies this model into the apparel - buying behavior and proposes the " systematical integrated model " in the apparel consumption decision - making. the author tends to find out the correspondent relationship between the different buying behaviors and their characteristics through the newest technique of data mining - - hybrid machine learning ( hml ). therefore, three sub - models on apparel consumption will be established

    本研究的立足點是心理學行為主義學派「刺激? ?反應」理論在服裝消費行為決策過程中的延伸，並在購買者行為模式的基礎上提出了服裝消費決策行為系統整合模型，筆者試圖通過系統整合的思想，採用數據挖掘的最新技術? ?混合機器學習（ hybridmachinelearning ，簡稱hml ）力圖找出具有不同購買反應的人群特徵的對應關系，即通過hml對所採集的數據庫的運行及其分析，構建上海地區服裝消費在「購買產品及其數量選擇」 、 「購買地點選擇」和「購買者確定」三個子模型，從而勾勒上海家庭服裝消費決策行為系統整合模型。
  15. In this paper, we adopt data mining technique and advance an integrative algorithm which establishs case base from traditional database

    採用了數據挖掘技術，提出了一個綜合演算法，從傳統數據庫中構造範例庫，以提高知識獲取的自動化程度。
  16. The data mining model combined with neural networks algorithm and genetic algorithm make the mf nodes arrangement and establishment location predictable and auto - adaptive under the future conditions

    採用神經網路與遺傳演算法相結合的數據挖掘模型，能夠使整個物流網路布局和設施選址對于未來的情況具有預測性和自適應性。
  17. With the boom of date mining, bayesian network has been paid great attention and again in the limeligh < because of the naturai relation between the mathematical statistics and data mining

    由於概率統計與數據採掘的天然聯系。數學采據興起后貝葉斯網路日益受到重視，再次成為引人注目的熱點
  18. Therefore, it is the same with data mining with probability statistic character and knowledge discovery problems, especially with die problems that obtain sample information or need high cost

    因此，適用於具有概率統計特徵的數據採掘和知識發現問題，尤其是樣本難以獲取或代價過于昂貴的問題。
  19. The modeling process is based on data mining technology, which can automatically discover the rules and knowledge in desulfuration process, and then provides the decision support, improves the desulfuration effect and decreases the cost. the successful use of this static model will be a solid prerequisite for full automatic dusulfuration in the future

    本文以國內某大型鋼鐵公司為背景，採用數據挖掘方法建立脫硫靜態模型，自動尋找脫硫過程的規律和知識，從而對脫硫過程進行決策支持，提高脫硫效果，降低脫硫成本，為全自動脫硫創造了良好的條件。
  20. Enterprise should take up client - oriented and client - based development plans. enterprises do n ' t attain loyalty of client and the most gain unless they know client necessity. so, the paper uses data mining technique to crm system and finds out model of client purchase in large client purchase by the analysis classification algorithm uptree. it provides meaningful comprehensive information for decision

    企業應採取面向客戶、客戶驅動和以客戶為中心的發展策略，企業只有真正了解客戶的需求，才有可能得到客戶的忠誠，才能獲得最大利益。為此，本文就是將數據挖掘技術應用於crm系統中，通過uptree演算法的研究，可以從大量客戶的購買行為中發現客戶購買模式，為決策者提供了有價值的商業信息。
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