Top-N Recommendation Model Based on SDAE

mortality forecasting based on lee-carter model

over the past decades a number of approaches have been applied for forecasting mortality. in 1992, a new method for long-run forecast of the level and age pattern of mortality was published by lee and carter. this method was welcomed by many authors so it was extended through a wider class of generalized, parametric and nonlinear model. this model represents one of the most influential recent d...

Suggest * Top-n Recommendation Engine

Content-Based Top-N Recommendation Using Heterogeneous Relations

Top-N recommender systems have been extensively studied. However, the sparsity of user-item activities has not been well resolved. While many hybrid systems were proposed to address the cold-start problem, the profile information has not been sufficiently leveraged. Furthermore, the heterogeneity of profiles between users and items intensifies the challenge. In this paper, we propose a content-...

Improving Top-N Recommendation with Heterogeneous Loss

Personalized top-N recommendation systems have great impact on many real world applications such as E-commerce platforms and social networks. Most existing methods produce personalized topN recommendations by minimizing a specific uniform loss such as pairwise ranking loss or pointwise recovery loss. In this paper, we propose a novel personalized top-N recommendation approach that minimizes a c...

Top-N Books Recommendation using Wikipedia

This paper presents an approach of recommending a ranked list of books to a user. A user profile is defined by a few liked and disliked books. To recommend a book, we calculate semantic relatedness of the given book to the liked and disliked books by using Wikipedia. Based on the obtained scores, we predict ratings of the book. We evaluate our approach on a dataset that consists of 6,181 users,...