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Permanent link (DOI): https://doi.org/10.7939/R3CC0V463

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Matrix and Tensor Approximation for Internet Latency Prediction and Online Purchase Prediction Open Access

Descriptions

Other title
Subject/Keyword
Network Latency Prediction
Online Purchase Prediction
Matrix Factorization
Type of item
Thesis
Degree grantor
University of Alberta
Author or creator
Liu, Bang
Supervisor and department
Di Niu (Electrical and Computer Engineering)
H. Vicky Zhao (Electrical and Computer Engineering)
Examining committee member and department
Hao Liang (Electrical and Computer Engineering)
H. Vicky Zhao (Electrical and Computer Engineering)
Linglong Kong (Mathematical and Statistical Sciences)
Di Niu (Electrical and Computer Engineering)
Department
Department of Electrical and Computer Engineering
Specialization
Computer Engineering
Date accepted
2015-09-03T10:16:55Z
Graduation date
2015-11
Degree
Master of Science
Degree level
Master's
Abstract
In this thesis, I study the application of matrix and tensor approximation techniques to Internet latency prediction and purchase prediction in e-commerce. Traditional approaches for latency prediction suffer from the limitation of the Euclidean assumptions such as triangle inequality and symmetric latencies. I propose a new scheme that can decompose an incomplete latency matrix into a distance component and a network feature component, and apply low-rank matrix completion to complete the network feature matrix based on the fact that network conditions are correlated. In the second problem, I analyze the user behavior records collected from Alibaba group's mobile B2C platform and propose a novel model, named Multifaceted Factorizing Personalized Markov Chains, to jointly factorize the tensor of purchase records into hidden factors for various context information. Extensive evaluations based on real-world datasets show that our proposed approaches outperform traditional approaches in both problems.
Language
English
DOI
doi:10.7939/R3CC0V463
Rights
Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.
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