Improved hybrid recommendation algorithm based on joint interpolation

التفاصيل البيبلوغرافية
العنوان: Improved hybrid recommendation algorithm based on joint interpolation
المؤلفون: Yang Su, QiChen Su, TianYi Liu
المصدر: Journal of Physics: Conference Series. 2024:012070
بيانات النشر: IOP Publishing, 2021.
سنة النشر: 2021
مصطلحات موضوعية: History, Similarity (network science), Computer science, Collaborative filtering, Rating matrix, Joint (audio engineering), Algorithm, Score matrix, Computer Science Applications, Education, Interpolation
الوصف: Aiming at the sparsity problem of the underlying score matrix of the collaborative filtering algorithm, to solve the problem of poor filling effect when the existing filling method has a large difference in the scores of items between neighbors, an improved hybrid recommendation algorithm based on joint interpolation is proposed. The algorithm first uses joint interpolation to fill in the user’s rating matrix, and then uses the similarity between the filled data and the user and item information to predict the user’s rating of the item, and then compares the item’s rating with the user’s scores of similar items, impose penalties on scores that are far apart, and finally recommend the penalized scores from high to low. Experimental results show that the algorithm has a better recommendation effect.
تدمد: 1742-6596
1742-6588
DOI: 10.1088/1742-6596/2024/1/012070
URL الوصول: https://explore.openaire.eu/search/publication?articleId=doi_________::2361022cb3c0646c99e08a032d62d281
https://doi.org/10.1088/1742-6596/2024/1/012070
Rights: OPEN
رقم الانضمام: edsair.doi...........2361022cb3c0646c99e08a032d62d281
قاعدة البيانات: OpenAIRE
الوصف
تدمد:17426596
17426588
DOI:10.1088/1742-6596/2024/1/012070