We propose a comprehensive, personalized multimedia recommendation system, denoted MudRecS, which makes recommendations on movies, music, books, and paintings ...

We propose a comprehensive, personalized multimedia recommendation system, denoted MudRecS, which makes recommendations on movies, music, books, and paintings ...

The performance ofMudRecS has been compared with current state-of-the-art multimedia recommenders using various multimedia datasets, and the experimental ...

Aug 12, 2012 · MudRecS predicts the ratings of multimedia items that match the in- terests of a user to make recommendations. The perfor- mance of MudRecS has ...

We propose a comprehensive, personalized multimedia recommendation system, denoted MudRecS, which makes recommendations on movies, music, books, and paintings ...

Predicting the ratings of multimedia items for making personalized recommendations ; The 35th International ACM SIGIR conference on research and development in ...

Predicting the ratings of multimedia items for making personalized recommendations. SIGIR, 2012. SIGIR 2012 · DBLP · Scholar · DOI. Full names. Links ISxN.

Nov 21, 2023 · This study improves the accuracy of ratings in recommendation systems through the combination of rating prediction and sentiment analysis from customer reviews.

Bibliographic details on Predicting the ratings of multimedia items for making personalized recommendations.

Nov 26, 2023 · The core of personalized content recommendations lies collaborative filtering — a foundational technique predicting user interests by ...