Application of clustering algorithm on TV programmes preference grouping of subscribers

With the development of digital cable interactive business and the diversification of the customers' demand, grouping TV programmes based on preferences of users effectively is vital for market segmentation and differentiation. The study summarizes the main principle and characteristic of clustering algorithm, and uses K-Means algorithm to show TV programmes preference grouping based on 52392 subscribers in a given area. Overall, the results show that K-Means algorithm is a better method to mine the data of television audience behavior; the clustering result could be a great guidance and the study lays a good foundation for analyzing TV user behavior.

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