本文選題：大數(shù)據(jù)分析　切入點：質(zhì)量功能展開　出處：《中國科技論壇》2017年12期 　論文類型：期刊論文

【摘要】：現(xiàn)有大數(shù)據(jù)分析方法存在側(cè)重算法提升而忽視數(shù)據(jù)固有關系、難以綜合分析網(wǎng)絡形態(tài)數(shù)據(jù)之間連動關系的問題。為解決這些問題,提出了一個基于擴展QFD和網(wǎng)絡圖的產(chǎn)品大數(shù)據(jù)分析方法。該方法由面向數(shù)據(jù)關系的擴展QFD、基于網(wǎng)絡圖的產(chǎn)品大數(shù)據(jù)關系描述模型和基于該描述模型的產(chǎn)品大數(shù)據(jù)分析模型組成。該方法有助于厘清產(chǎn)品各類數(shù)據(jù)間的固有關系,可將具有復雜結(jié)構(gòu)、多重關系的數(shù)據(jù)以清晰的網(wǎng)絡結(jié)構(gòu)表現(xiàn)出來,并可綜合利用多種大數(shù)據(jù)分析模型對產(chǎn)品大數(shù)據(jù)進行模式探索,從而達到從海量數(shù)據(jù)中獲取關鍵數(shù)據(jù)、發(fā)現(xiàn)新數(shù)據(jù)及數(shù)據(jù)間的新關系等目標。解決了現(xiàn)有大數(shù)據(jù)分析方法忽視數(shù)據(jù)固有關系、難以綜合分析數(shù)據(jù)間連動關系的問題,使數(shù)據(jù)建模與算法技術更好地結(jié)合。
[Abstract]:The existing big data analysis methods focus on algorithm upgrading and ignore the inherent relationship of data, so it is difficult to comprehensively analyze the linkage relationship between network morphological data. In order to solve these problems, In this paper, a product big data analysis method based on extended QFD and network diagram is proposed. Analysis of model composition. This method helps to clarify the inherent relationships between the various types of product data, The data with complex structure and multiple relationships can be represented by a clear network structure, and various big data analysis models can be comprehensively used to explore the pattern of the product big data, so as to obtain the key data from the massive data. It solves the problem that the existing big data analysis methods ignore the inherent relationship of data, and it is difficult to analyze the relationship between the data, so that the data modeling and algorithm technology can be combined better.
【作者單位】： 北京工業(yè)大學經(jīng)濟與管理學院北京現(xiàn)代制造業(yè)發(fā)展研究基地;
【基金】：國家自然科學基金面上項目“基于類比推理的短生命周期無形體驗品需求預測”(71672004)
【分類號】：TP311.13
，

本文編號：1649092