数据与计算发展前沿 ›› 2021, Vol. 3 ›› Issue (5): 141-155.

doi: 10.11871/jfdc.issn.2096-742X.2021.05.011

• 技术与应用 • 上一篇    

大数据驱动的创新方法论与创新服务平台

鹿旭东1(),宋伟凤1(),郭伟1(),崔立真1,*(),林岳2(),姜涛1()   

  1. 1.山东大学软件学院,山东 济南 250101
    2.北京亿维讯同创科技有限公司,北京 100025
  • 收稿日期:2020-12-15 出版日期:2021-10-20 发布日期:2021-11-24
  • 通讯作者: 崔立真
  • 作者简介:鹿旭东,山东大学软件学院,博士,讲师,硕士生导师,主要研究方向为软件工程、用户界面模型、智能数据分析等。
    本文主要承担系统方案的设计与实现。
    LU Xudong, Ph.D., is a lecturer and master supervisor in the School of Software, Shandong Univer-sity. His main research directions are software engine-ering, user interface models, intelligent data analysis, etc.
    In this paper, he is mainly responsible for the design and implementation of the system scheme.
    E-mail: dongxul@sdu.edu.cn|宋伟凤,山东大学软件学院,硕士研究生,主要研究方向为大数据科学与工程、智能数据分析等。
    本文主要承担论文的写作与部分系统的实现。
    SONG Weifeng is a master student in the School of Software, Shandong Un-iversity. Her main research fields are big data science and engineering, intelligent data analysis, etc.
    In this paper, she is mainly responsible for the writing of the thesis and the realization of parts of the system.
    E-mail: swf.1987@163.com|郭伟,山东大学软件学院,工程师,硕士生导师,主要研究方向为云计算数据管理、智能数据分析等。
    本文主要承担系统方案的设计设计与实现。
    GUO Wei is an engineer and master supervisor in the School of Software, Shandong University. His main research directions are cloud computing data mana-gement, intelligent data analysis, etc.
    In this paper, he mainly undertakes the design and implemen-tation of the system scheme.
    E-mail: guowei@sdu.edu.cn|崔立真,山东大学软件学院,教授,博士生导师,山东大学软件学院院长,山东大学- 南洋理工大学人工智能国际联合研究院(C-FAIR)联合院长,电子商务交易技术国家工程实验室副主任。主要研究方向为大数据科学与工程、智能数据分析与大图深度学习、服务计算与协同计算等。
    本文主要承担系统方案的设计与实现。
    CUI Lizhen, the professor, is a doctoral supervisor in the School of Software, Shandong University. He is appointed as dean and deputy party secretary for School of Software in Shandong University, co-director of Joint SDU-NTU Centre for Artificial Intelligence Research(C-FAIR), and the associ-ate director of the National Engineering Laboratory for E-Comm-erce Transaction Technologies. His main research directions are big data science and engineering, intelligent data analysis and deep learning of big graphs, service computing, and collab-orative computing, etc.
    In this paper, he is mainly responsible for the design and imple-mentation of the system scheme.
    E-mail: clz@sdu.edu.cn|林岳,博士,高级工程师。现任北京亿维讯同创科技有限公司总经理,中国创新方法研究会高新技术企业创新方法应用分会理事长,主要负责在企业特别是高新技术企业中开展创新方法的推广用工作。目前正在开展复杂装备产品创新设计方法学理论以及应用研究、大中型企业的创新方法推广应用模式范式以及多种创新方法在企业中的融合研究。
    本文主要承担系统方案的设计与实现。
    LIN Yue, Ph.D., is titled a senior engineer. He is currently the general manager of Beijing IWINT Technology Co., Ltd., and the chairman of the China Innovation Method Research Association High-tech Enterprise Innovation Method Appli-cation Branch. He is mainly responsible for the promotion of innovative methods in enterprises, especially high-tech enterprises. At present, he is researching the theory and application of innovative design methodologies of complex equipment products, the promotion and application model paradigm of innovative methods of large and medium-sized enterprises, and the integration of multiple innovative methods in enterprises.
    In this paper, he is mainly responsible for the design and implementation of the system scheme.
    E-mail: alp.lin@iwintall.com|姜涛,山东大学软件学院,硕士研究生,主要研究方向为大数据科学与工程、智能数据分析、自然语言处理等。
    本文主要承担论文的写作与部分系统的实现
    JIANG Tao is a master student in the School of Software, Shandong Univ-ersity. His main research fields are big data science and engineering, intelligent data analysis, natural language processing, etc.
    In this paper, he is mainly responsible for the writing of the thesis and the realization of parts of the system.
    E-mail: jiangtao_smart@163.com
  • 基金资助:
    国家创新方法工作专项资助(2020IM020100);国家创新方法工作专项资助(2018IM020200);国家创新方法工作专项资助(2015IM020200);山东省自然科学基金重大基础研究项目(ZR2017ZB0420)

Big Data Driven Innovation Methodology and Innovation Service Platform

LU Xudong1(),SONG Weifeng1(),GUO Wei1(),CUI Lizhen1,*(),LIN Yue2(),JIANG Tao1()   

  1. 1. Software College, Shandong University, Jinan, Shandong 250101, China
    2. Beijing Yiweixun Tongchuang Technology Co., Ltd., Beijing 100025, China
  • Received:2020-12-15 Online:2021-10-20 Published:2021-11-24
  • Contact: CUI Lizhen

摘要:

【目的】本文提出了一种大数据驱动的创新方法论并研制了大数据驱动创新服务平台。【应用背景】针对大众创新过程中,难以应用系统化的创新方法,难以处理信息碎片化等问题。【方法】基于大数据技术和众智汇聚的思想;以多源创新数据的跨界融合为基础,构建创新方法大数据和创新知识图谱;通过社会化公众参与和互动反馈,形成汇聚众智的创新模式;基于创新大数据知识图谱,实现创意自动快速引导生成;基于发明原理等创新方法理论,在大众参与下实现创新方案的形成。【结果】本文研究成果已经在工业制造、互联网产品研发等多个行业中应用,通过大量案例证明了所提出方法论和创新服务平台的有效性。【结论】大数据驱动的创新方法论和创新服务平台为创新提供了思维、方法和工具支持,通过对数据挖掘和众智科学的研究,智能地解决了创新面临的难题,推动创新向着智能化、大众化方向发展。

关键词: 大数据驱动, 创新方法, 众智, 众创, 服务平台

Abstract:

[Objective] This paper proposes a big data driven innovation methodology and develops the corresponding service platform. [Context] It is difficult to apply systematic innovation methods and deal with information fragmentation in the process of mass innovation. [Methods] Based on big data technology and the idea of gathering intelligence, this paper has constructed an innovative method of big data and innovative knowledge graph by the integration of multi-source cross-industry innovative data. Through socialized public participation and interactive feedback, an innovative model that gathers all wisdom is formed. Based on the innovative big data knowledge graph, new ideas can be generated and realized automatically and rapidly. Based on the theory of innovation methods such as the principle of invention, the formation of innovative solutions is realized with the participation of the public. [Results] The proposed methodology and platform have been applied in many industries such as research and development of industrial manufacturing and Internet products. A large number of cases have proved the effectiveness of the proposed methodology and innovative service platform. [Conclusions] The big data driven innovation methodology and innovation service platform provide mindsets, methods and tools support for innovation. Through the research on data mining and crowd science, problems faced by innovation can be intelligently solved, and innovation is promoted towards intelligence and popularization.

Key words: big data driven, innovation methodology, crowd wisdom, crowd creation, service platform