An Integration Model on Brainstorming and Extenics for Intelligent Innovation in Big Data Environment

IF 0.5 4区 计算机科学 Q4 COMPUTER SCIENCE, SOFTWARE ENGINEERING
Xingsen Li, Haibin Pi, Junwen Sun, Hao Lan Zhang, Zhencheng Liang
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引用次数: 0

Abstract

Brainstorming is a widely used problem-solving method that generates a large number of innovative ideas by guiding and stimulating intuitive and divergent thinking. However, in practice, the method is limited by the human brain's capacity or special capabilities, especially by the experience and knowledge they possess. How does our brain create ideas like storming? Based on the new discipline of Extenics, the authors propose a new model that explores the process of how ideas are created in our brain, with the goal of helping people think multi-dimensionally and getting more ideas. With the support of information technology and artificial intelligence, we can systematically collect more information and knowledge than ever before to form a basic-element information base and build human-computer interaction models, to make up for the lack of information and knowledge in the human brain. In addition, the authors provide a methodology to help people think positively in a multidimensional way based on the guidance of Extenics in the brainstorming process.
大数据环境下智能创新的头脑风暴与可拓集成模型
头脑风暴是一种广泛使用的解决问题的方法,它通过引导和激发直觉思维和发散思维来产生大量的创新想法。然而,在实践中,这种方法受到人类大脑容量或特殊能力的限制,特别是受到他们所拥有的经验和知识的限制。我们的大脑是如何产生像风暴这样的想法的?基于可拓学的新学科,作者提出了一个新的模型,探索想法是如何在我们的大脑中产生的过程,目的是帮助人们多维度思考,获得更多的想法。在信息技术和人工智能的支持下,我们可以系统地收集比以往更多的信息和知识,形成基本要素信息库,构建人机交互模型,弥补人脑中信息和知识的不足。此外,作者还提供了一种方法,帮助人们在头脑风暴过程中以可拓学的指导为基础,以多维度的方式积极思考。
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来源期刊
International Journal of Data Warehousing and Mining
International Journal of Data Warehousing and Mining COMPUTER SCIENCE, SOFTWARE ENGINEERING-
CiteScore
2.40
自引率
0.00%
发文量
20
审稿时长
>12 weeks
期刊介绍: The International Journal of Data Warehousing and Mining (IJDWM) disseminates the latest international research findings in the areas of data management and analyzation. IJDWM provides a forum for state-of-the-art developments and research, as well as current innovative activities focusing on the integration between the fields of data warehousing and data mining. Emphasizing applicability to real world problems, this journal meets the needs of both academic researchers and practicing IT professionals.The journal is devoted to the publications of high quality papers on theoretical developments and practical applications in data warehousing and data mining. Original research papers, state-of-the-art reviews, and technical notes are invited for publications. The journal accepts paper submission of any work relevant to data warehousing and data mining. Special attention will be given to papers focusing on mining of data from data warehouses; integration of databases, data warehousing, and data mining; and holistic approaches to mining and archiving
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