Time Series Clustering Model based on Complexity for Apple Technology Forecasting
نویسنده
چکیده
The technologies developed by Apple have led the technological innovations in the world. So many studies on the technology analysis of Apple were performed in diverse fields of academic and business. In addition, the research results of Apple technology analysis using the quantitative methods such as statistics and machine learning algorithms were performed. They were the objective approaches to understand the technological innovation of Apple, provided meaningful findings of Apple technology. But they did not consider the time trend of the developed technologies. The time periods are important issue in technological development. So in this paper, we propose a technology forecasting of Apple according to time trend of each technology. We use time series clustering based on complexity to build technology forecasting model of Apple innovation. To show how the proposed methodology can be applied to real problem, we perform a case study using the all patent documents applied by Apple.
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