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New Radio and Television Program Collaborative Recommendation Process Based on TF-IDF

  

  1. (1. School of Geophysics & Measurement-control Technology, East China University of Technology, Nanchang 330013, China;
    2. School of Chemical Biology & Materials Science, East China University of Technology, Nanchang 330013, China;
    3. School of Science, East China University of Technology, Nanchang 330013, China)
  • Received:2018-11-29 Online:2019-09-23 Published:2019-09-23

Abstract: With the rapid development of Internet technology and application expansion, triple play (Internet, telecommunication network, broadcast TV network) has brought development opportunities for traditional broadcast TV media. However, with the increase of data size, the existing recommendation algorithm does not meet the expected requirements for the accurate recommendation of many “category” broadcast TV users, and has obvious deficiencies. In this paper, based on the similarity between users and the similarity between products, Pearson correlation coefficient, TF-IDF-based cosine similarity and collaborative recommendation are used to construct two algorithm flows that can be accurately recommended for new broadcast TV users, and can get accurate classification and accurate delivery of products.

Key words: collaborative filtering, recommendation system, TF-IDF, new radio and television program, cosine similarity

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