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OALib Journal期刊
ISSN: 2333-9721
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PROMOTING AND POSITIONING ENTERTAINMENT ARTISTS USING CLUSTERING AND CLASSIFICATION APPROACHES

Keywords: Technology Forecasting , Artist Clustering , Artificial Neural Networks (Ann) , Career Path Planning , Talent Management

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Abstract:

The entertainment industry is undergoing significant transformation and growth. The goal of the entertainment agency is to establish and manage the careers of individual artists. This research develops an approach to evaluate the potential of entertainment artists and construct individualized career maps. Data mining techniques are used to correlate the entertainment news on the Internet with the degree of exposure and success of the artists. Technology forecast methods are applied to predict potential career paths for new artists. Thus, entertainment agencies can assess the value of artists and plan appropriate marketing strategies as well as attract talented artists utilizing scientific and systematic approaches. The proposed methodology can also be applied to sports and other creative arts industries that rely on individual talents developed over time.

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