Essays about: "matrix factorization"

Showing result 1 - 5 of 54 essays containing the words matrix factorization.

1. 1. Recommending digital books to children : Acomparative study of different state-of-the-art recommendation system techniques

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Malvin Lundqvist; [2023]
   Keywords : Recommendation Systems; Collaborative Filtering; Matrix Factorization; Multi-Layer Perceptron; Neural Network-based Collaborative Filtering; Implicit Feedback; Deep Learning; Term Frequency-Inverse Document Frequency; Rekommendationssystem; Kollaborativ filtrering; Matrisfaktorisering; Flerlagersperceptron; Neurala nätverksbaserad kollaborativ filtrering; Implicit data; Djupinlärning; Termfrekvens med omvänd dokumentfrekvens;

   Abstract : Collaborative filtering is a popular technique to use behavior data in the form of user’s interactions with, or ratings of, items in a system to provide personalized recommendations of items to the user. This study compares three different state-of-the-art Recommendation System models that implement this technique, Matrix Factorization, Multi-layer Perceptron and Neural Matrix Factorization, using behavior data from a digital book platform for children. READ MORE

3. 2. Evolving Community Detection in Dynamic Networks using Nonnegative Tensor Decomposition : An Approach Toward Green Networking

   University essay from Luleå tekniska universitet/Datavetenskap

   Author : Manasik Hassan Adam Ali; [2023]
   Keywords : ;

   Abstract : Around 1.8–2.8% of the world’s total greenhouse gas emissions are contributed by the ICT sector, with telecommunications networks accounting for 26.4% of this total ICT share. READ MORE

4. 3. Minimum Cost Distributed Computing using Sparse Matrix Factorization

   University essay from KTH/Optimeringslära och systemteori

   Author : Seif Hussein; [2023]
   Keywords : Applied mathematics; optimization; convex optimization; matrix factorization; sparse matrix factorization; distributed computing; linearly separable distributed computing; ADMM; alternating direction method of multipliers; tillämpad matematik; optimering; konvex optimering; matrisfaktorisering; gles matrisfaktorisering; distribuerade beräkningar; admm; alternating direction method of multipliers;

   Abstract : Distributed computing is an approach where computationally heavy problems are broken down into more manageable sub-tasks, which can then be distributed across a number of different computers or servers, allowing for increased efficiency through parallelization. This thesis explores an established distributed computing setting, in which the computationally heavy task involves a number of users requesting a linearly separable function to be computed across several servers. READ MORE

5. 4. Dimensionality Reduction in High-Dimensional Profile Analysis Using Scores

   University essay from Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakulteten

   Author : Jonathan Vikbladh; [2022]
   Keywords : High-dimensional data; Hypothesis testing; LR test; Linear scores; Multivariate analysis; Profile analysis; Spherical distributions;

   Abstract : Profile analysis is a multivariate statistical method for comparing the mean vectors for different groups. It consists of three tests, they are the tests for parallelism, level and flatness. The results from each test give information about the behaviour of the groups and the variables in the groups. READ MORE

6. 5. Predicting future purchases with matrix factorization

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Azer Hojlas; August Paulsrud; [2022]
   Keywords : Matrix factorisation; machine learning; recommendations systems; Maskininlärning; Matrisfaktorisering; Rekommendationssystem;

   Abstract : This thesis aims to establish the efficacy of using matrix factorization to predict future purchases. Matrix factorisation is a machine learning method, commonly used to implement the collaborative filtering recommendation system. READ MORE