Cerca risorse accademiche

Sistem rekomendasi telah diterapkan dalam digital marketing yang digunakan dalam pemasaran produk dan jasa. Sistem rekomendasi digunakan untuk memberikan penawaran barang maupun jasa sesuai dengan kebiasaan dan minat pel...

Recommender systems have been evaluated in many, often incomparable, ways. In this article, we review the key decisions in evaluating collaborative filtering recommender systems: the user tasks being evaluated, the types...

In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks on recommender systems has recei...

Automated Collaborative Filtering (CF) techniques have been successfully applied on Recommendation domains. Dellarocas [1] proposes their use on reputation domains to provide more reliable and personalized reputation est...

We propose a novel image denoising strategy based on an enhanced sparse representation in transform domain. The enhancement of the sparsity is achieved by grouping similar 2-D image fragments (e.g., blocks) into 3-D data...

Recommender systems apply knowledge discovery techniques to the problem of making personalized recommendations for information, products or services during a liveinteraction. These systems, especially the k-nearest neigh...

This research paper introduces UniEats, a recipe recommendation website designed to help university students better organize their meals and adopt healthier eating habits. The system aims to address common challenges stu...

The rapid growth of e-commerce has led to product overload, which has resulted in personalized product discovery becoming a crucial problem for consumers. Classic recommender systems (RS), which rely heavily on content-b...

Isu Smart Taourism (Wisata Pintar) memiliki topik populer dalam beberapa waktu terakhir, hasil ini dalam peningkatan jumlah prototipe pariwisata aplikasi desktop berbasis web dan berbasis mobile. Penelitian ini berfokus ...

The necessity for sophisticated recommender systems in the movie recommendation sphere has become particularly pronounced, generating a more personalized movie recommendation due to people nowadays who like to watch movi...

Maintaining a balanced diet is essential for overall well-being, yet many individuals face challenges in meal planning due to time constraints, limited nutritional knowledge, and difficulty aligning meals with personal d...

Abstract Collaborative filtering and neural recommendation models have advanced substantially over the past decade, yet they frequently struggle to capture the fine-grained structure of user preferences and the rich, mul...

"The steel industry faces increasing challenges in managing product diversity, maintaining competitiveness, and improving operational efficiency. Within this context, recommendation systems present a promising opportunit...

"En la era del turismo digital, las recomendaciones personalizadas se han vuelto esenciales para mejorar la experiencia del viajero. Esta tesis investiga el desarrollo de un sistema de recomendación turística utilizand...

We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collection ...

IntroductionGender equity remains a central issue in contemporary research and public policy, shaped by structural, cultural, and institutional inequalities. Despite increased academic attention, the field continues to e...

Infrared thermal radiation signals are highly susceptible to environmental interference, leading to dynamic fluctuations. Consequently, weak targets are frequently submerged in heavy clutter backgrounds under extreme sce...

This paper presents an overview of the field of recommender systems and describes the current generation of recommendation methods that are usually classified into the following three main categories: content-based, coll...