Related papers: Matrix Factorization for Cache Optimization in Con…

A Content Delivery Network (CDN) is a powerful system of distributed caching servers that aims to accelerate content delivery, like high-definition video, IoT applications, and ultra-low-latency services, efficiently and with fast velocity.…

The importance of content delivery networks (CDN) continues to rise with the exponential increase in the generation and consumption of electronic media. In order to ensure a high quality of experience, CDNs often deploy cache servers that…

Matrix factorization (MF) is extensively used to mine the user preference from explicit ratings in recommender systems. However, the reliability of explicit ratings is not always consistent, because many factors may affect the user's final…

Depth factorization and quantization have emerged as two of the principal strategies for designing efficient deep convolutional neural network (CNN) architectures tailored for low-power inference on the edge. However, there is still little…

Recommender systems are emerging technologies that nowadays can be found in many applications such as Amazon, Netflix, and so on. These systems help users to find relevant information, recommendations, and their preferred items. Slightly…

Content-Centric Networking (CCN) offers a novel architectural paradigm that seeks to address the inherent limitations of the prevailing Internet Protocol (IP)-based networking model. In contrast to the host-centric communication approach of…

Data often comes in the form of an array or matrix. Matrix factorization techniques attempt to recover missing or corrupted entries by assuming that the matrix can be written as the product of two low-rank matrices. In other words, matrix…

Content delivery networks (CDNs) are the backbone of the Internet and are key in delivering high quality video on demand (VoD), web content and file services to billions of users. CDNs usually consist of hierarchically organized content…

Internet video traffic has been been rapidly increasing and is further expected to increase with the emerging 5G applications such as higher definition videos, IoT and augmented/virtual reality applications. As end-users consume video in…

Content Centric Networking (CCN) is a recent advancement in communication networks where the current research is mainly focusing on routing & cache management strategies of CCN. Nonetheless, other perspectives such as network level security…

Information Centric Networking (ICN) is a new network architecture (Internet) that focuses on content rather than the end-hosts. Named Data Networking (NDN) is a specific implementation of ICN, which relies on the use of named data and a…

In this paper, I explore the potential of network embedding (a.k.a. graph representation learning) to characterize DNS entities in passive network traffic logs. I propose an MF-DNS-E (\underline{M}atrix-\underline{F}actorization-based…

Content-Centric Networking (CCN) is a new class of network architectures designed to address some key limitations of the current IP-based Internet. One of its main features is in-network content caching, which allows requests for content to…

Recommendation Systems apply Information Retrieval techniques to select the online information relevant to a given user. Collaborative Filtering is currently most widely used approach to build Recommendation System. CF techniques uses the…

Nonnegative Matrix Factorization (NMF) aims to factorize a matrix into two optimized nonnegative matrices and has been widely used for unsupervised learning tasks such as product recommendation based on a rating matrix. However, although…

Matrix factorization models are the core of current commercial collaborative filtering Recommender Systems. This paper tested six representative matrix factorization models, using four collaborative filtering datasets. Experiments have…

Matrix factorization techniques have been widely used as a method for collaborative filtering for recommender systems. In recent times, different variants of deep learning algorithms have been explored in this setting to improve the task of…

This research investigates how CDNs (Content Delivery Networks) can improve the digital experience, as consumers increasingly expect fast, efficient, and effortless access to online resources. CDNs play a crucial role in reducing latency,…

The goal of Content Delivery Networks (CDNs) is to serve content to end-users with high performance. In order to do that, a CDN measures the latency on the paths from its servers to users and then selects a best available server for each…

In-network caching is one of the fundamental operations of Information-centric networks (ICN). The default caching strategy taken by most of the current ICN proposals is caching along--default--path, which makes popular objects to be cached…