association between data 中文意思是什麼

association between data 解釋
數據結合
  • association : n 1 聯合；聯系；聯盟；合夥；交際，交往。2 社團，協會；學會。3 【生物學】群落，社會。4 聯想。5 【...
  • between : adv 當中，中間。 two windows with a door between 兩扇窗戶當中有一扇門。 We could not see the moon...
  • data : n 1 資料，材料〈此詞系 datum 的復數。但 datum 罕用，一般即以 data 作為集合詞，在口語中往往用單數...
  1. This paper analysis the data mining of the single nd multiple streams time series, and draw a conclusion that the relationship between the events of the multiple streams time series are the association patterns dependency patterns, sudden patterns, this paper call them are structure patterns, the existing algorithm have n ' t discuss these patterns, although msdd discussed the dependency patterns, however, it ignored the association patterns, sudden patterns, this paper have a definition of the association patterns, sudden patterns and dependency patterns, and have a complete, frank algorithm called twma ( time window moving and filtering algorithm ), the peculiarity of this algorithm is that events is listed by the time window, by this way, the relationship of the events is clear

    本文將它們統稱為結構模式，而這正是目前其它演算法、沒有考慮到的，雖然msdd考慮了事件之間的依賴關系，但它忽略了突變模式，關聯模式等重要的知識表示。本文給出了關聯模式、依賴模式、突變模式的定義，提出了一個比較靈活全面、直觀的挖掘它們的演算法：時間窗口移動篩選演算法twma （ timewindowmovingandfilteringalgorithm ） 。該演算法的一個突出特點是將時間序列事件按時間窗口序列化，使得事件之間的時間關系表示很直觀，該演算法能成功地從多流時間序列中發現了事件之間的關系。
  2. Background : the association between benign anal lesions and anal cancer is still unclear. few data from large cohort studies are aailable

    背景：良性肛門損傷和肛門癌之間的聯系還不清除。尚缺乏有效的大規模的群組分析數據。
  3. Association rules mining, as the most important subject in data mining, reveals the corelations between itemsets and therefore can be widely applied to many fields such as market basket analysis, corelation analysis, classification, web - customised service, etc. since 1993 when r. agrawal, r. srikant firstly proposed the concept of association rules, a lot of algorithms have come up in mining of association rules

    關聯規則揭示項集間有趣的相聯關系，可廣泛應用於購物籃分析、相關分析、分類、網路個性化服務等領域，是數據挖掘的重要研究課題。自1993年r . agrawal ， r . srikant首次提出該問題以來，已出現了許多關聯規則挖掘演算法。
  4. Mining data between people characters and their actions is a important aspect for multidimensional association rules. for example, association trend between students ' s nature information and their behavior. but many general mining tools have not paid much attention to these aspects

    對于群體的特徵與行為的數據挖掘是關聯規則挖掘的一種重要的也是復雜的挖掘方向。例如在學生系統中的學生個體自然信息與他們的選課行為傾向之間的關聯傾向，商業領域中的顧客基本信息與購買傾向也屬于這類情況。
  5. Whereas many researchers tried to forecast the impacts of climatic changes on future societies, few attempted to scrutinize quantitatively using historical data the association between climatic changes and social developments. to fill this knowledge gap, this study adopted a scientific approach to compare high - resolution palaeo - climatic records with historical data of wars, social unrests, and dynastic transitions in china spanning from the late tang to qing dynasties

    西方學者把這種現象用朝代循環論（ dynasticcycle ）來解釋，把朝代興亡、社會定亂、經濟盛衰等幾方面，完全歸結為社會演化和管理失誤；其他社會科學家們也常常從政治、經濟、文化、民族沖突方面尋找戰爭的原因。
  6. Using the qtdt ( quantitative trait transmission disequilibrium test ), we did not find significant results for association or linkage between the ahsg gene and bmd variation at the spine or hip. our data did not provide evidence to support the ahsg gene as a quantitative trait locus ( qtl ) for the bmd variation in a chinese population

    通過數量性狀傳遞不平衡法（ quantitativetraittransmissiondisequilibriumtest ， qtdt ） ，沒有檢測到ahsg基因與腰椎和髖部骨密度變異之間明顯的關聯或連鎖，因此我們的數據不支持ahsg基因是中國人群中導致骨密度變異的數量性狀位點（ quantitativetraitlocus ， qtl ） 。
  7. In this paper, data mining techniques based on spatial database, especially gis database, are studied, of which spatial data classification based on rough set theory and spatial association rule mining are studied in detail. the differences between mining in spatial database and in relational database are analyzed

    本文以基於空間數據庫特別是gis數據庫的數據挖掘技術為研究對象，主要研究了基於rough集理論的空間數據分類和空間關聯規則挖掘技術，分析了在空間數據庫與在關系數據庫中進行數據挖掘的區別。
  8. Association rule mining is an important sub - branch of data mining, which describes the potential relationships between attributes and variables in databases

    關聯規則挖掘是數據挖掘的一個重要分支，是描述數據庫中數據項（屬性、變量）間存在的潛在關系。
  9. According these, slope engineering can be done. then, researches the relation between rainfall and slope, including two sides : one is relating water infiltration and soil state by soil ' s water content to show that slope situates most disadvantage circumstances when rainfall comes. the other is showing the relation between rainfall and slope by data from monitor. last, applies grey system to the slope, including gm model forecasting and grey association analysis

    然後對滑坡和降雨之間的關系進行研究，包括兩方面，一是利用土體含水量將雨水的入滲和土體的飽和非飽和狀態聯系起來，驗證了暴雨或者持續降雨來臨時土體處于最不利情況。二是通過實測的降雨量和位移速率關系，來直觀表現滑坡和降雨的關系。
  10. 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。
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