质量嵌入的大数据产品生产系统超图模型及其生产线决策研究
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摘要
大数据产品(Big Data Product,BDP)在原材料、用户需求、加工工艺等方面具有不同于实体产品的特征,而现有BDP生产系统的研究仍停留在概念模型阶段。为了解决该问题,提出BDP生产线的概念,基于生产线特征研究了生产线决策要素,强调了质量作为关键决策要素在BDP生产中的作用机理;采用超图理论建立了嵌入质量、质量传递函数和质量聚集函数的BDP生产系统模型,设计了BDP生产线决策流程;提出了供给侧稳定和需求侧稳定的BDP生产线决策模式。实例验证结果表明,所提出的模型和决策方法能够满足用户对BDP质量的要求。
Due to the different characteristics of the Big Data Product(BDP)in terms of raw materials,user requirements,and processing techniques,research on BDP production system still stays at the conceptual model stage.To solve this problem,this paper purposed the concept of BDP production lines,discussed the decision factors for production line selection based on the characteristics of production line,and emphasized the action mechanism of quality as a key decision element in BDP production.This paper established the BDP production system model embedded with quality,quality transfer function and quality aggregation function by using the hypergraph theory,designed the decision processes for BDP production line,and proposed the decision mode of the BDP production line with supply-side-stable and demandside-stable.The results show that the proposed model and decision method can meet users' requirements for BDP quality.
Due to the different characteristics of the Big Data Product(BDP)in terms of raw materials,user requirements,and processing techniques,research on BDP production system still stays at the conceptual model stage.To solve this problem,this paper purposed the concept of BDP production lines,discussed the decision factors for production line selection based on the characteristics of production line,and emphasized the action mechanism of quality as a key decision element in BDP production.This paper established the BDP production system model embedded with quality,quality transfer function and quality aggregation function by using the hypergraph theory,designed the decision processes for BDP production line,and proposed the decision mode of the BDP production line with supply-side-stable and demandside-stable.The results show that the proposed model and decision method can meet users' requirements for BDP quality.
引文
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[30]CHENG W,WANG B,LI Z H,et al.Study on Optimization Matching Method Oriented to E-platform for Investment and Financing[J].Journal of Chongqing University of Technology(Natural Science),2011,25(5):75-81.(in Chinese)成卫,王奔,李战华,等.一种面向电子商务投融资平台的优化匹配方法[J].重庆理工大学学报(自然科学),2011,25(5):75-81.
[2] JIN X,WAH B W,CHENG X,et al.Significance and challenges of big data research[J].Big Data Research,2015,2(2):59-64.
[3] WANG R Y,LEE Y W,PIPINO L L,et al.Manage your information as a product[J].Sloan Management Review,1998,39(4):95-105.
[4] DAVENPORT T H,KUDYBA S.Designing and developing analytics-based data products[J].MIT Sloan Management Review,2016,58(1):83-89.
[5] CHAO L M,XING C X,ZHANG Y.Data science studies:Stateof-the-art and trends[J].Computer Science,2018,45(1):1-13.(in Chinese)朝乐门,邢春晓,张勇.数据科学研究的现状与趋势[J].计算机科学,2018,45(1):1-13.
[6] BALLOU D,WANG R,PAZER H,et al.Modeling information manufacturing systems to determine information product quality[J].Management Science,1998,44(4):462-484.
[7] LEE Y,CHASE S,FISHER J,et al.CEIPMaps:Context-embedded information product maps[C]∥Proceedings of the 13th Americas Conference on Information Systems(AMCIS 2007).Association for Information Systems,2007.
[8] MEYER M H,ZACK M H.The design and development of information products[J].Sloan Management Review,1996,37(3):43-59.
[9] CAI S Q,MA Y T,XIAO Q,et al.Research on mapping for designing product family of user-generated content based on hypergraph design model[J].Journal of the China Society for Scientific and Technical Information,2011,30(4):387-394.(in Chinese)蔡淑琴,马玉涛,肖泉,等.基于超图设计模型的用户创造内容产品族设计映射研究[J].情报学报,2011,30(4):387-394.
[10]YAQOOB I,HASHEM I A,GANI A,et al.Big data:From beginning to future[J].International Journal of Information Management,2016,36(6):1231-1247.
[11]JURAN J M.Juran on quality by design:The new steps for planning quality into goods and services[M].New York:The Free Press,1992.
[12]LIU J,ZHAO S Z.Research on dynamic development model information product quality assesment[J].Computer Science,2015,42(1):244-248.(in Chinses)刘婧,赵嵩正.信息产品质量测量动态衍变模型研究[J].计算机科学,2015,42(1):244-248.
[13]HUANG D M,ZHAO D F,WEI L F,et al.Managing marine data as big data:uprising challenges and tentative solutions[J].Computer Science,2016,43(6):17-23.(in Chinese)黄冬梅,赵丹枫,魏立斐,等.大数据背景下海洋数据管理的挑战与对策[J].计算机科学,2016,43(6):17-23.
[14]SAHA B,SRIVASTAVA D.Data quality:The other face of big data[C]∥Proceedings of the IEEE 30th International Conference on Data Engineering.IEEE,2014:1294-1297.
[15]PARSSIAN A,SARKAR S,JACOB V S.Assessing data quality for information products:Impact of selection,projection,and cartesian product[J].Management Science,2004,50(7):967-982.
[16]SHANKARANARAYANAN G,BLAKE R.From content to context:The evolution and growth of data quality research[J].Journal of Data and Information Quality,2017,8(2).
[17]KLEINDIENST D.The data quality improvement plan:Deciding on choice and sequence of data quality improvements[J].Electronic Markets,2017,27(4):387-398.
[18]WATSON H J.Tutorial:Big data analytics:Concepts,technologies,and applications[J].Communications of the Association for Information Systems,2014,34(1):1247-1268.
[19] WOODALL P.The data repurposing challenge:New pressures from data analytics[J].ACM Journal of Data and Information Quality,2017,8(3-4):11.
[20]RICCI F,LIOR R,BRACHA S.Introduction to recommender systems handbook[M].US:Springer,2011:1-35.
[21]PANG B,LILLIAN L.Opinion mining and sentiment analysis[J].Foundations and Trends in Information Retrieval,2008,2(1-2):1-135.
[22]LEE Y W,PIPINO L L,FUNK J D,et al.Journey to data quality[M].Cambridge,USA:The MIT Press,2006.
[23]BATINI C,CAPPIELLO C,FRANCALANCI C,et al.Methodologies for data quality assessment and improvement[J].ACM Computing Surveys,2009,41(3):1-52.
[24]TODORAN I G,LECORNU L,KHENCHAF A,et al.A methodology to evaluate important dimensions of information quality in systems[J].Journal of Data and Information Quality,2015,6(2-3):11:1-11:23.
[25]RAJAGOPALAN R,BATRA J.Design of cellular production systems a graph-theoretic approach[J].The International Journal of Production Research,1975,13(6):567-579.
[26]LIU P,LI Y,ZHANG K F.Layered orientation graph modeling method for assembly of complex products[J].Journal of Machine Design,2007,24(4):30-32.(in Chinese)刘平,李原,张开富.复杂产品装配的分层有向图建模方法[J].机械设计,2007,24(4):30-32.
[27]PURKAIT P,CHIN T J,SADRI A,et al.Clustering with hypergraphs:The case for large hyperedges[J].IEEE Transactions on Pattern Analysis and Machine Intelligence,2017,39(9):1697-711.
[28]KONSTAS I,LAPATA M.Unsupervised concept-to-text generation with hypergraphs[C]∥Proceedings of the 2012Conference of the North American Chapter of the Association for Computational Linguistics:Human Language Technologies.Association for Computational Linguistics,2012:752-761.
[29]WANG Y,WU Y,CAI S.A hypergraph model for market opportunity discovery[C]∥Proceedings of the Fourth International Joint Conference on Computational Sciences and Optimization.IEEE,2011:322-326.
[30]CHENG W,WANG B,LI Z H,et al.Study on Optimization Matching Method Oriented to E-platform for Investment and Financing[J].Journal of Chongqing University of Technology(Natural Science),2011,25(5):75-81.(in Chinese)成卫,王奔,李战华,等.一种面向电子商务投融资平台的优化匹配方法[J].重庆理工大学学报(自然科学),2011,25(5):75-81.