An Extension Collaborative Innovation Model in the Context of Big Data

Xingsen Li (), Yingjie Tian (), Florentin Smarandache () and Rajan Alex ()
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Xingsen Li: School of Management, Ningbo Institute of Technology, Zhejiang University, Ningbo 315100, P. R. China
Yingjie Tian: Research Center on Fictitious Economy and Data Science, CAS, Beijing 100190, P. R. China
Florentin Smarandache: Mathematics and Science Department, University of New Mexico, Gallup, NM 87301, USA
Rajan Alex: School of Engineering and Computer Science, West Texas A&M University, Conyon, TX 79015, USA

International Journal of Information Technology & Decision Making (IJITDM), 2015, vol. 14, issue 01, 69-91

Abstract: The processes of generating innovative solutions mostly rely on skilled experts who are usually unavailable and their outcomes have uncertainty. Computer science and information technology are changing the innovation environment and accumulating Big Data from which a lot of knowledge is to be discovered. However, it is a rather nebulous area and there still remain several challenging problems to integrate the multi-information and rough knowledge effectively to support the process of innovation. Based on the new cross disciplineExtenics, the authors have presented a collaborative innovation model in the context of Big Data. The model has two mutual paths, one to transform collected data into an information tree in a uniform basic-element format and another to discover knowledge by data mining, save the rules in a knowledge base, and then explore the innovation paths and solutions by a formularized model based onExtenics. Finally, all possible solutions are scored and selected by 3D-dependent function. The model which integrates different departments to put forward the innovation solutions is proved valuable for a user of the Big Data by a practical innovation case in management.

Keywords: Extension innovation model; Big Data; data mining; Extenics; knowledge management (search for similar items in EconPapers)
Date: 2015
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Citations: View citations in EconPapers (3)

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DOI: 10.1142/S0219622014500266

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