Book recommender mobile application / Amir Imran Kamaludin

In this age where information is vast and huge, it is found to be difficult to find the right information from the enormous amount of data that is present and growing in the online platforms. Recommendation system solves this problem by automatically sorting through the massive amounts of data and i...

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Bibliographic Details
Main Author:	Kamaludin, Amir Imran
Format:	Thesis
Language:	English
Published:	2021
Subjects:	Electronic Computers Computer Science Android Algorithms
Online Access:	https://ir.uitm.edu.my/id/eprint/58883/1/58883.pdf
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id	my-uitm-ir.58883
record_format	uketd_dc
spelling	my-uitm-ir.588832022-07-28T08:09:30Z Book recommender mobile application / Amir Imran Kamaludin 2021-02 Kamaludin, Amir Imran Electronic Computers. Computer Science Android Algorithms In this age where information is vast and huge, it is found to be difficult to find the right information from the enormous amount of data that is present and growing in the online platforms. Recommendation system solves this problem by automatically sorting through the massive amounts of data and identify user’s interest and makes the information searching much more easily. In this project, it presented a model for a personalized collaborative filtering book recommendation system. It are takes some information from user through signup which will help to get more appropriate recommendations based on individual user item rating and thus an attempt to overcome cold start problem. The item based collaborative filtering are used in this system with Cosine based similarity algorithm as the main algorithm. 2021-02 Thesis https://ir.uitm.edu.my/id/eprint/58883/ https://ir.uitm.edu.my/id/eprint/58883/1/58883.pdf text en public degree Universiti Teknologi MARA, Perak Faculty of Computer and Mathematical Sciences Nik Mustapa, Nik Ruslawati
institution	Universiti Teknologi MARA
collection	UiTM Institutional Repository
language	English
advisor	Nik Mustapa, Nik Ruslawati
topic	Electronic Computers Computer Science Android Algorithms
spellingShingle	Electronic Computers Computer Science Android Algorithms Kamaludin, Amir Imran Book recommender mobile application / Amir Imran Kamaludin
description	In this age where information is vast and huge, it is found to be difficult to find the right information from the enormous amount of data that is present and growing in the online platforms. Recommendation system solves this problem by automatically sorting through the massive amounts of data and identify user’s interest and makes the information searching much more easily. In this project, it presented a model for a personalized collaborative filtering book recommendation system. It are takes some information from user through signup which will help to get more appropriate recommendations based on individual user item rating and thus an attempt to overcome cold start problem. The item based collaborative filtering are used in this system with Cosine based similarity algorithm as the main algorithm.
format	Thesis
qualification_level	Bachelor degree
author	Kamaludin, Amir Imran
author_facet	Kamaludin, Amir Imran
author_sort	Kamaludin, Amir Imran
title	Book recommender mobile application / Amir Imran Kamaludin
title_short	Book recommender mobile application / Amir Imran Kamaludin
title_full	Book recommender mobile application / Amir Imran Kamaludin
title_fullStr	Book recommender mobile application / Amir Imran Kamaludin
title_full_unstemmed	Book recommender mobile application / Amir Imran Kamaludin
title_sort	book recommender mobile application / amir imran kamaludin
granting_institution	Universiti Teknologi MARA, Perak
granting_department	Faculty of Computer and Mathematical Sciences
publishDate	2021
url	https://ir.uitm.edu.my/id/eprint/58883/1/58883.pdf
_version_	1783735005638295552

Book recommender mobile application / Amir Imran Kamaludin

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