用叉挖掘 的英文怎麼說
中文拼音 [yòngchāwājué]
用叉挖掘
英文
forking-
This paper presents the directed itemsets graph to store the information of frequent itemsets of transaction databases, and puts forward the trifurcate linked list storage structure of directed itemsets graph, and provides the mining algorithm of frequent closed itemsets based on directed itemsets graph
摘要利用了有向項集圖來存儲事務數據庫中有關頻繁項集的信息，提出了有向項集圖的三叉鏈表式存儲結構和在於有向項集圖的頻繁閉項集挖掘演算法。( 2000 ). the neutron irradiation is assumed to derive primarily by the reaction 13c ( a, n ) i60 with a minor contribution from the marginal burning of 22ne through the channel 22ne ( a n ) 23mg in the final, high temprature phase of each flash. and we considered the influence of the various parameters such as the initial core mass, the envelope mass, the mass - loss rate, the overlap factor and the delution factor etc., and we vary their value with the pulse number
本文採用分叉s -過程反應通道，以~ （ 13 ） c （ ， n ） ~ （ 16 ） o 、 ~ （ 22 ） ne （ ， n ） ~ （ 25 ） mg為雙脈沖中子源，用最新的中子俘獲截面，利用gallino和busso等人給出的agb星三殼層核合成模型，考慮到核心質量、挖掘程度、重疊因子、稀釋因子及星風質量損失率隨脈沖數的變化，詳細計算和研究了各個金屬豐度情況下的3m 。Mining the information about discipline intercrossing from citation index data
利用引文索引數據挖掘學科交叉信息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。These machines include fork - lift trucks used in industrial undertakings, bulldozers, loaders, excavators, trucks and lorries used on construction sites
這些機械包括在工業經營中使用的叉式起重車及在建築地盤使用的推土機、搬土機、挖掘機、卡車及貨車。In short, the innovations of this research can be concluded as fomowings : ( 1 ) to take the lead in applying the newest data mining technique based - on the artificial intelligence in the traditional apparel expenditure behavior, which is not only unique in angle of view but also creative in the research methodology ; ( 2 ) to integrate each aspect of the household apparel consumption decision - making behavior within one system, then to apply the outcome into market practice ; ( 3 ) to take use of both the traditional statistic methods and data mining technique based - on hml to analysis apparel consumption decision - making behavior, which learn from others " strong points to offset one ' s weakness and achieve mastery through a comprehensive study of the subject
具體邇一言，本研究的創新之處可以歸納為: （ 1 ）率先將基於人工智慧的數據挖掘最新技術和成果應用於傳統的服裝消費行為的研究，不僅視角獨特而且在消費行為研究的方法論上有所突破。 （ 2 ）利用數據挖掘工具將家庭服裝消費行為的各個方面進行了系統的整合研究，突破了傳統研究的單一性和局部性，從而挖掘真正代表消費者購買傾向的規則和模式，並將研究結果應用於市場實際操作加以驗證，實現理論與實踐的結合。 （ 3 ）將以數理統計為中心的傳統統計方法與以市場數據為中心的數據挖掘技術方法交叉應用於服裝消費行為的實際問題研究，取長補短，融會貫通。Similarity - based crossover - mutation operator and its application to mining classification rules
基於相似度的交叉變異運算元及其在分類規則挖掘中的應用Data mining is the process of abstracting unaware, potential and useful information and knowledge from plentiful, incomplete, noisy, fuzzy and stochastic data, which is deemed to one of a foreland of data mining system and a promising cross - subject. cluster analysis is one of the most important research domains of data mining
數據挖掘是從大量的、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，被信息產業界認為是數據庫系統最重要的前沿之一，是信息產業最有前途的交叉學科。The data mining techniques produce and develop quickly under the application environment. they can converse the sea data into the useful knowledge automatically and intelligently. the discovering methods synthesize the research achievements in the fields including expert system, machine learning, statistics, pattern recognition, database, etc. they can resolve the problems in the information and in favor of data ' s conversion
數據挖掘技術是一門交叉性學科，涉及到機器學習、模式識別、歸納推理、統計學、數據庫、數據可視化、高性能計算等多個領域，對解決在信息技術發展中存在的擁有大量數據但缺乏有用信息的問題，以及完成從業務數據到決策信息的轉換方面具有較強的功效。分享友人