knowledge discovery in databases 中文意思是什麼

knowledge discovery in databases 解釋
知識發現
  • 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。
  • discovery : n. 1. 發見，發現，發覺。2. 〈古語〉顯示，暴露，顯露。3. （劇情的）發展。4. 被發現的事物。5. 【法律】（審判前當事一方必須作出的）顯示證據。
  • in : adv 1 朝里，向內，在內。 A coat with a furry side in有皮裡子的外衣。 Come in please 請進來。 The ...
  • databases : 數據庫
  1. Kdd ( knowledge discovery in databases ) can find out the effective, novel, latent, and apprehensible information

    知識發現（ kdd ）能夠從數據庫中識別出有效的、新穎的、潛在有用的、以及最終可理解的信息。
  2. Knowledge discovery in databases ( kdd ) is a multidisciplinary field, drawing work from areas including database technology, artificial intelligence, machine learning, statistics, neural networks, and pattern recognition

    數據庫中的知識發現（ knowledgediscoveryindatabases ， kdd ）是當前涉及人工智慧、數據庫等學科的一門非常活躍的研究領域。
  3. Data mining and knowledge discovery in databases is a new technology for drawing knowledge from data

    數據挖掘和知識發現是從數據中獲取知識的一種新技術。
  4. One of these challenges is to enable users to get the maximum benefit from the data they stored. data mining and knowledge discovery in databases ( kdd ) is an international frontier and has already become a hotspot hi r & d field

    數據挖掘與從數據庫中發現知識是在對更深入、更充分的開發信息資源的迫切需求背景下產生並迅速發展起來的一個國際前沿領域，它已經成為研究的一個熱點。
  5. So, knowledge discovery in databases emerges, as the times require

    因此，數據庫中的知識發現這一研究熱點就應運而生了。
  6. In the fourth european conference on principles and practice of knowledge discovery in databases, france, 2000, pp. 424 - 431. 3 d d lewis. naive bayes at forty : the independence assumption in information retrieval

    在非監督環境下，概念索引concept index ， ci尋找相似文本簇，並把文本簇的中心作為低維空間的坐標來構建低維數據空間。
  7. 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
  8. In the data extracting stage, aiming at interfacing of knowledge discovery algorithms to large database management systems, we present a family of generic, set - based, primitive operations for knowledge discovery in databases. we show how a number of well - known kdd classification algorithms can all be computed via our generic data extractors

    該介面利用一組基於sql語言的數據抽取器實現為數據挖掘演算法抽取必要的統計數據，避免了直接對大型數據庫的數據進行調用，使得對大型數據庫進行快速數據挖掘成為可能。
  9. 2 ) in this paper, we present a novel qrrecl model. because it denotes the extension and intension of concept in the compact form and shows the relations among the concepts more clearly, it is a more efficient tool for knowledge discovery especially in large databases

    2 ）提出了量化相對約簡格模型，它以最簡形式表示概念的內涵和外延，更清晰地反映了概念之間的依賴關系，有利於更有效地從大規模數據庫中進行知識的發現。
  10. Based on the uci knowledge discovery in databases archive and uci machine learning archive as experiment data, works developed in this thesis as follows : 1. this thesis studies the current kdd model, and suggests a kdd model based data extractor

    針對目前的知識發現過程模型在實際應用中存在挖掘周期長，對大型數據庫的知識發現支持不夠的問題，提出了基於數據抽取器的知識發現模型。
  11. O conceptual hierarchies organization technique concepts in databases are organized into a partial order called conceptual hierarchies. conceptual hierarchies play an important role in the knowledge discovery process because they specify backgroud or domain knowledge and may affect the discovery processing and the results. ln this paper, basic ideas about conceptual hierarchy and its manipulation are discussed. based on the conceptual hierarchies in the nms database, we present processing methods o application research of multilevel association algorithm in the nms database we emphatically discuss performance data multilevel conceptual association problems on network management background, especially, the association between performance data and geographic location. after studying encoding multilevel association algorithms and background item constraint algorithms, an efficient mining multilevel association algorithm between performance data and geographic location is presented. lt is efficient for mining useful association rules

    一旁多級關聯演算法在網路數據庫中的應用本文重點研究了網路管理背景下多級概念下性能數據關聯問題，特別是性能數據和地理位置關聯的問題。將概念結構方法應用於網路管理數據庫之中。通過對編碼結構實現的多級關聯技術的研究，通過對網路管理數據庫下背景知識約束條件實現研究，提出了」一種高效的，網路管理性能數據與地理位置關聯的挖掘演算法。
分享友人
分享到 Line

分享到臉書