Mar 25, 2016 · Through data analysis, we observe that users having similar attributes tend to share more similar preferences and users with a special attribute ...
This paper uses the movie rating data from MovieLens as an example to show how to use users' attributes to improve the accuracy of rating prediction, ...
Through data analysis, we observe that users having similar attributes tend to share more similar preferences and users with a special attribute have their own ...
Sep 21, 2020 · The article focuses on Deep Cooperative Neural Networks (DeepCoNN), taking reviews from users and items for the rating prediction problems. In ...
As user and item attributes describe user and item content information, given the complete attribute feature vector of each user (item), attribute enhanced ...
Aug 18, 2020 · In this paper, we present a joint deep recommendation model (JDRM) that consists of two parallel neural networks, learning lower-order feature interactions of ...
Col- laborative filtering makes use of past ratings of the target user, the target item and other user-item rat- ings to predict the target user's rating on the ...
Missing: Attributes | Show results with:Attributes
In this paper, we propose a joint model that incorporates review text information with matrix factorization for review rating prediction.
Attribute-aware CF models aim at rating prediction given not only the historical rating given by users to items but also the information associated with users ( ...
Latent factor model (LFM), which uses a dot product between the resulting user and item latent factors to rank candidate items, is the most popular ...