knowledge extraction 中文意思是什麼

knowledge extraction 解釋
知識提取
  • knowledge : n. 1. 知識；學識，學問。2. 了解，理解；消息。3. 認識。4. 〈古語〉學科。5. 〈古語〉性關系。
  • extraction : n. 1. 抽出，拔出。2. 【化學】提取（法）；萃取（法）；回收物，提出物；精煉。3. 精選，摘要。4. 血統，家世，出身。5. 【數學】開方，求根。
  1. In these bases, a mutual knowledge extraction system is programmed

    在此基礎上，編程實現了一個互動式的知識抽取系統。
  2. Diagnostic knowledge extraction based on variable precision rough - fuzzy sets integration model

    模糊集模型的診斷知識獲取
  3. Applying rough sets a knowledge extraction methodology for agents is introduced

    提出一種基於粗糙集的agent知識獲取方法。
  4. The evolution of om and web knowledge extraction effectively promote open integration of knowledge

    Om （組織記憶）的進化和web知識抽取有效地促進了知識的開放性集成。
  5. The open integration of knowledge depends on knowledge conversion, knowledge extraction and knowledge stanchion

    知識的開放性集成依賴于知識轉換、知識抽取和知識標注。
  6. Therefore, a study of incremental data mining algorithm is urgently needed. incremental data mining only modifies rule sets when database is updated, which takes advantage of previous calculation result and prevents knowledge extraction from the very beginning

    把增量演算法與數據庫的更新結合在一起，漸增地進行知識的更新、修正和加強先前業已發現的知識，這樣可以不必重新挖掘全部數據。
  7. As a novel tool for knowledge extraction, the rough set theory can supply reliable data to maintenance technicians for rapid and effective fault diagnosis by the " reduction " of information system and extracting a set of minimal diagnostic conditions in the fault diagnosis system

    應用粗糙集理論挖掘工具，對故障信息系統「約簡」 ，在故障診斷系統中提取最小診斷條件集，可為設備維護人員提供快捷、有效的診斷依據。
  8. ( 1 ) for methodological syncretization of emi and km, existing reference architectures ( ras ) do not clearly reflect the level characteristics of enterprise knowledge and its organization and application modes. ( 2 ) for enterprise knowledge capture and application, existing enterprise modeling methods face the dilemma of how to facilitate friendly collaboration and communication between system analysts / developers and enterprise staffs, and how to help system analysts / developers utilize model knowledge to carry out effective quantitative analysis. ( 3 ) for knowledge re - use, it lacks powerful knowledge repository systems for enterprise model re - use and corresponding mechanisms for knowledge extraction, classification and index

    目前國內外關于該方向的研究尚處于起步階段，有許多問題亟待解決，主要表現在：在企業集成與知識管理的方法論融合方面，現有參考體系結構沒有很好地反映出企業知識的層次特徵及其組織、應用方式；在企業知識的收集與應用方面，現有企業建模方法在如何促進系統分析設計人員與企業人員進行友好的合作與交流和如何幫助系統分析設計人員利用模型知識進行有效的定量分析這兩個問題上存在著矛盾；在知識重用方面，缺乏面向企業模型重用的功能完備的知識庫系統及相應的知識提煉和分類檢索機制，能夠被業界廣泛接受的參考模型尚不多見；在建立面向企業集成的基於知識的系統方面，尚沒有很好地解決知識的形式化表示問題，缺乏用於描述企業深層知識的形式化建模手段。
  9. In cbt courseware development platform, many function and application are supported by multimedia knowledge database. the text language knowledge is the most basic knowledge form, so text knowledge automatism extraction becomes the key technique in the cbt courseware development. the paper mostly introduces how the knowledge extraction system is designed and realize in the cbt courseware development

    在cbt （ computerbasedtraining ）課件開發平臺中，很多的功能和應用都是以多媒體知識庫為后臺支持的，其中文本語言知識是最基本的知識形式，因此文本知識自動抽取成為cbt課件開發中的關鍵技術之一。
  10. To support end - user - programming and reuse composition knowledge, this paper discusses the key problems of how to extract, manage and reuse the composition knowledge in the service - oriented applications, and presents a service composition template based approach to larger - granularity business - level composition knowledge management and initiative recommendation - trybest, the main research work and contribution of this dissertation is described as follows : ( 1 ) proposed a novel approach to service composition knowledge management and recommendation - trybest we introduce the thinking of software reuse into composition knowledge extraction and use ; propose an approach to service composition knowledge extraction by using make use of the technology of case based rule and vinca process

    在業務端編程思想和面向最終用戶編程的vinca語言已有工作的基礎上，從支持最終用戶編程、對組合知識復用的角度出發，提出了面向業務用戶的基於服務組合模板的大粒度業務級組合知識的管理與主動推薦方法? ? trybest ，通過對服務組合中組合知識的抽取、管理和復用，為最終業務用戶主動參與面向服務的應用構造提供支持。主要工作和貢獻如下:提出了一種支持復用的服務組合知識管理和主動推薦方法? ? trybest 。
  11. Based on knowledge reasoning, fuzzy theory, extraction of sub - assembly and cluster, and hierarchical connection relation graph, an assembly sequence generation algorithm is studied in this paper, which breaks down the original complex assembly sequence generation problem into several small scale assembly sequence planning problems to reduce the computing complexity caused by cut - set theory. a hierarchical and / or graph to store all the generated sequences is also employed for this purpose

    本文提出基於知識推理及模糊理論，結合子裝配與聚族提取以及裝配樹，利用層次聯接關系圖，將一個復雜的裝配序列求解問題轉化為若干個相關的小規模裝配序列求解問題，並用一種層次與或圖結構存儲裝配序列，使割集法求解裝配序列的計算復雜度大大降低。
  12. With the development of informatics, the data about tcm began more than ever. so the work on data cleaning and extraction began complex and difficult. how to discover the knowledge about tcm in huge database, how to diagnose the symptom complex from symptoms and how to effective compound the prescription for traditional chinese doctor are the three important problems

    隨著信息化的深入，中醫藥信息越來越多，對其整理和歸納的工作也越來越復雜：如何從中找到有用的中醫藥知識；如何利用以前的臨床案例來進行中醫證侯的診斷；如何利用巨大的方劑知識，為中醫專家有效地提供新的方劑配伍，是三個急需解決的問題。
  13. Based on orl, we generate knowledge extract rules by induce learning, by which we realize the dynamic extraction to outer knowledge, and then realize the automatic generation of knowledge item. by this mean, we strengthen the opened - knowledge - integration of system. 3

    本文以orl語言為基礎，通過定義文檔本體並對文檔內容進行解析，歸納學習生成知識提取規則，實現了對文檔知識的自動抽取，並以之為輔助工具，實現了知識項的自動建立，強化了系統的「知識開放性集成」 。
  14. 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。
  15. Firstly, influence factors of generalization of neural network are presented in this thesis, in order to improve neural network ’ s generalization ability and dynamic knowledge acquirement adaptive ability, a structure auto - adaptive neural network new model based on genetic algorithm is proposed to optimize structure parameter of nn including hidden layer nodes, training epochs, initial weights, and so on ; secondly, through establishing integrating neural network and introducing data fusion technique, the integrality and precision of acquired knowledge is greatly improved. then aiming at the incompleteness and uncertainty problem consisting in the process of knowledge acquirement, knowledge acquirement method based on rough sets is explored to fulfill the rule extraction for intelligent diagnosis expert system, by completing missing value data and eliminating unnecessary attributes, discretization of continuous attribute, reducing redundancy, extracting rules in this thesis. finally, rough sets theory and neural network are combined to form rnn ( rough neural network ) model for acquiring knowledge, in which rough sets theory is employed to carry out some preprocessing and neural network is acted as one role of dynamic knowledge acquirement, and rnn can improve the speed and quality of knowledge acquirement greatly

    本文首先討論了影響神經網路的泛化能力的因素，提出了一種新的結構自適應神經網路學習演算法，在新方法中，採用了遺傳演算法對神經網路的結構參數（隱層節點數、訓練精度、初始權值）進行優化，大大提高了神經網路的泛化能力和知識動態獲取自適應能力;其次，構造集成神經網路，引入數據融合演算法，實現了基於集成神經網路的融合診斷，有效地提高了知識獲取的全面性、完善性及精度;然後，針對知識獲取過程中所存在的不確定性、不完備性等問題，探討了運用粗糙集理論的知識獲取方法，通過缺損數據補齊、連續數據的離散、沖突消除、冗餘信息約簡、知識規則抽取等一系列的演算法實現了智能診斷的知識規則獲取;最後，將粗糙集理論與神經網路相結合，研究了粗糙集-神經網路的知識獲取方法。
  16. Data mining means the process of nontrivial extraction of implicit, previous unknown and potentially useful information and knowledge from the large amount, incomplete, noisy, fuzzy and random data

    數據挖掘，指的是從大量的、不完全的、有噪聲的、模糊的、隨機的數據中，提取隱含在其中的、人們事先不知道的、但又是潛在有用的信息和知識的過程。
  17. Pca & flda ), knowledge - based methods and neural - networks based methods, etc. in this thesis two novel classes of feature extraction methods are proposed, i. e. matrix - pattern - based and vector subpattern - based representation methods respectively

    在本文中，我們在pca和flda方法的基礎上提出了兩類特徵提取新方法，即基於矩陣模式和基於子向量的特徵提取方法，並隨後用于模式的分類。
  18. For the first time this dissertation discusses the feasibility of data mining for the fields data of cfbb ， analyses the preprocessing technology of sample data ， introduces the application of clustering analysis ， and finally completes the rule extraction by applying knowledge - based artificial neural network. considering distributed parameters ， nonlinear ， and long time lag system of cfbb ， the theory of self - organizing neural fuzzy inference system is applied to the control system of cfbb ， and enables control rules extraction on - line. the models of data mining and self - organizing ( fbnc - pnn controller ) are programmed ， embedded to the control system of a 35 t / h cfbb in tsingtao ， and finally improve the performance of cfbb effectively

    本文還針對流化床鍋爐運行的非線性嚴重、大滯后、不確定性大等特點，研究了基於數據挖掘優化的模糊神經自組織控制策略在循環流化床控制系統中的應用，使規則獲取可以在線進行；並編制了數據挖掘模塊優化自組織控制模塊，應用到青島35t / h循環流化床鍋爐的控制系統中，提高了鍋爐的運行水平和效率，取得了良好的效果。
  19. The main point of this project is to research the theories and applications of artificial neural network ( ann ) which is suitable for large scale science data mining. especially, our research focus include : dimension reduction techniques based on independent component analysis ( ica ) and wavelet - based denoising or compressing techniques for feature extraction in scientific datasets which have complex features ; classify and clustering techniques of ann combination with data grid, back - propagation neural network, self - growing multilevel self - organizing map for large scale knowledge founding in sdm

    特別深入研究以獨立分量分析（ ica ）為主的降維技術、以小波神經網路為主的壓縮降噪技術解決科學數據特徵復雜不便識別的問題;以同網格結合的神經網路、誤差反向傳播的bp神經網路、自適應多級自組織特徵映像網路為主的分類、聚類技術解決科學數據挖掘中的大規模知識發現問題。
  20. Based on analyzing the relationship between linear separability and a connected set in boolean space, the particular effect of a restraining neuron in extraction of rules from a bnn is discussed, and that effect is explained through a example called a mis problem in boolean space. in this paper, a pattern match learning algorithm of bnns is proposed. when a bnn has been trained by the algorithm, all the binary neurons of hidden layer belong to one or more ls series, if the logical meanings of those ls series are clear, the knowledge in the bnn can be dug out

    另一個研究成果是在分析線性可分和樣本連通性關系的基礎上，以mis問題為例，討論了抑制神經元在二進神經網路規則提取中的獨特作用，提出了二進神經網路的模式匹配學習演算法，採用這種演算法對布爾空間的樣本集合進行學習，得到的二進神經網路隱層神經元都歸屬於一類或幾類線性可分結構系，只要這幾類線性可分結構系的邏輯意義是清晰的，就可以分析整個學習結果的知識內涵。
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