Optimize Ranking System With Machine Learning

This thesis investigates how recommendation systems has been used and can be used with the help of different machine learning algorithms. Algorithms used and presented are decision tree, random forest and singular-value decomposition(SVD). Together with Tingstad, we have tried to implement the SVD f...

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Bibliographic Details
Main Authors: Mattsson, Fredrik, Gustafsson, Anton
Format: Others
Language:English
Published: Högskolan i Halmstad, Akademin för informationsteknologi 2018
Subjects:
ML
B2B
SVD
Online Access:http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-37431
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spelling ndltd-UPSALLA1-oai-DiVA.org-hh-374312018-07-03T05:58:05ZOptimize Ranking System With Machine LearningengMattsson, FredrikGustafsson, AntonHögskolan i Halmstad, Akademin för informationsteknologiHögskolan i Halmstad, Akademin för informationsteknologi2018MLB2BMachine learningSVDDecision treeComputer SciencesDatavetenskap (datalogi)This thesis investigates how recommendation systems has been used and can be used with the help of different machine learning algorithms. Algorithms used and presented are decision tree, random forest and singular-value decomposition(SVD). Together with Tingstad, we have tried to implement the SVD function on their recommendation engine in order to enhance the recommendation given. A trivial presentation on how the algorithms work. General information about machine learning and how we tried to implement it with Tingstad’s data. Implementations with Netflix’s and Movielens open-source dataset was done, estimated with RMSE and MAE. Student thesisinfo:eu-repo/semantics/bachelorThesistexthttp://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-37431application/pdfinfo:eu-repo/semantics/openAccess
collection NDLTD
language English
format Others
sources NDLTD
topic ML
B2B
Machine learning
SVD
Decision tree
Computer Sciences
Datavetenskap (datalogi)
spellingShingle ML
B2B
Machine learning
SVD
Decision tree
Computer Sciences
Datavetenskap (datalogi)
Mattsson, Fredrik
Gustafsson, Anton
Optimize Ranking System With Machine Learning
description This thesis investigates how recommendation systems has been used and can be used with the help of different machine learning algorithms. Algorithms used and presented are decision tree, random forest and singular-value decomposition(SVD). Together with Tingstad, we have tried to implement the SVD function on their recommendation engine in order to enhance the recommendation given. A trivial presentation on how the algorithms work. General information about machine learning and how we tried to implement it with Tingstad’s data. Implementations with Netflix’s and Movielens open-source dataset was done, estimated with RMSE and MAE.
author Mattsson, Fredrik
Gustafsson, Anton
author_facet Mattsson, Fredrik
Gustafsson, Anton
author_sort Mattsson, Fredrik
title Optimize Ranking System With Machine Learning
title_short Optimize Ranking System With Machine Learning
title_full Optimize Ranking System With Machine Learning
title_fullStr Optimize Ranking System With Machine Learning
title_full_unstemmed Optimize Ranking System With Machine Learning
title_sort optimize ranking system with machine learning
publisher Högskolan i Halmstad, Akademin för informationsteknologi
publishDate 2018
url http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-37431
work_keys_str_mv AT mattssonfredrik optimizerankingsystemwithmachinelearning
AT gustafssonanton optimizerankingsystemwithmachinelearning
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