Essays about: "Matrix Factorization"
Showing result 1 - 5 of 54 essays containing the words Matrix Factorization.
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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)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
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2. Evolving Community Detection in Dynamic Networks using Nonnegative Tensor Decomposition : An Approach Toward Green Networking
University essay from Luleå tekniska universitet/DatavetenskapAbstract : 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
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3. Minimum Cost Distributed Computing using Sparse Matrix Factorization
University essay from KTH/Optimeringslära och systemteoriAbstract : 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
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4. Dimensionality Reduction in High-Dimensional Profile Analysis Using Scores
University essay from Linköpings universitet/Tillämpad matematik; Linköpings universitet/Tekniska fakultetenAbstract : 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
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5. Predicting future purchases with matrix factorization
University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)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