A collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining

A collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining

Nowadays, tourism industry are actively being utilised in generating a state or country income. In order to attract tourist from all over places, information conveyance is important. Traditionally, people travels to certain places based on oral recommendation by families and friends. Now, people ten...

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Main Author: Zolhani, Nur Azleen
Format: Thesis
Language:English
English
Published: 2015
Subjects:
Q Science (General)
QA Mathematics
QA76 Computer software
Online Access:http://eprints.utem.edu.my/id/eprint/15893/1/A%20COLLABOTIVE%20FILTERING%20RECOMMENDER%20SYSTEM%20FOR%20INFREQUENTLY%20PURCHASED%20PRODUCT%20USING%20SLOPE-ONE%20ALGORITHM%20AND%20ASSOCIATION%20RULE%20MINING%20%2824%20pgs%29.pdf
http://eprints.utem.edu.my/id/eprint/15893/2/A%20collaborative%20filtering%20recommender%20system%20for%20infrequently%20purchased%20product%20using%20slope-one%20algorithm%20and%20association%20rule%20mining.pdf
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id my-utem-ep.15893
record_format uketd_dc
institution Universiti Teknikal Malaysia Melaka
collection UTeM Repository
language English
English
advisor Abdullah, Noraswaliza
topic Q Science (General)
QA Mathematics
QA76 Computer software
spellingShingle Q Science (General)
QA Mathematics
QA76 Computer software
Zolhani, Nur Azleen
A collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining
description Nowadays, tourism industry are actively being utilised in generating a state or country income. In order to attract tourist from all over places, information conveyance is important. Traditionally, people travels to certain places based on oral recommendation by families and friends. Now, people tends to go travel based on reviews that are read from blogs and websites. But, this leads to overflow of unfiltered information. In order to effectively recommending places to travel for tourist, recommendation engine are being developed. Most recommendation engine has suffice information to make recommendation for example Amazon.com recommendation and Google.com recommendation. Meanwhile, in tourism it is quite challenging in making recommendation because hotels are occasionally being booked or purchased by consumer. This is due to the fact that travelling are expensive and time consuming. This project implement the collaborative filtering using slope-one algorithm and also implement association rule mining in recommending hotels for tourist. This recommender system uses slope-one algorithm whereby it accumulate and takes into account of the difference in popularity. The objective of this project to study different types of recommendation techniques for infrequently purchased products and to investigate technique and dataset that are suitable to implement in recommending infrequently purchased products. As a conclusion, this collaborative filtering recommendation system will help user in decision making. Further research on other approaches in implementing recommender system in tourism domain can help in information delivery.
format Thesis
qualification_name Master of Philosophy (M.Phil.)
qualification_level Master's degree
author Zolhani, Nur Azleen
author_facet Zolhani, Nur Azleen
author_sort Zolhani, Nur Azleen
title A collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining
title_short A collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining
title_full A collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining
title_fullStr A collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining
title_full_unstemmed A collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining
title_sort collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining
granting_institution Universiti Teknikal Malaysia Melaka
granting_department Faculty of Information and Communication Technology
publishDate 2015
url http://eprints.utem.edu.my/id/eprint/15893/1/A%20COLLABOTIVE%20FILTERING%20RECOMMENDER%20SYSTEM%20FOR%20INFREQUENTLY%20PURCHASED%20PRODUCT%20USING%20SLOPE-ONE%20ALGORITHM%20AND%20ASSOCIATION%20RULE%20MINING%20%2824%20pgs%29.pdf
http://eprints.utem.edu.my/id/eprint/15893/2/A%20collaborative%20filtering%20recommender%20system%20for%20infrequently%20purchased%20product%20using%20slope-one%20algorithm%20and%20association%20rule%20mining.pdf
_version_ 1747833882546274304
spelling my-utem-ep.158932022-04-20T10:49:43Z A collaborative filtering recommender system for infrequently purchased product using slope-one algorithm and association rule mining 2015 Zolhani, Nur Azleen Q Science (General) QA Mathematics QA76 Computer software Nowadays, tourism industry are actively being utilised in generating a state or country income. In order to attract tourist from all over places, information conveyance is important. Traditionally, people travels to certain places based on oral recommendation by families and friends. Now, people tends to go travel based on reviews that are read from blogs and websites. But, this leads to overflow of unfiltered information. In order to effectively recommending places to travel for tourist, recommendation engine are being developed. Most recommendation engine has suffice information to make recommendation for example Amazon.com recommendation and Google.com recommendation. Meanwhile, in tourism it is quite challenging in making recommendation because hotels are occasionally being booked or purchased by consumer. This is due to the fact that travelling are expensive and time consuming. This project implement the collaborative filtering using slope-one algorithm and also implement association rule mining in recommending hotels for tourist. This recommender system uses slope-one algorithm whereby it accumulate and takes into account of the difference in popularity. The objective of this project to study different types of recommendation techniques for infrequently purchased products and to investigate technique and dataset that are suitable to implement in recommending infrequently purchased products. As a conclusion, this collaborative filtering recommendation system will help user in decision making. Further research on other approaches in implementing recommender system in tourism domain can help in information delivery. 2015 Thesis http://eprints.utem.edu.my/id/eprint/15893/ http://eprints.utem.edu.my/id/eprint/15893/1/A%20COLLABOTIVE%20FILTERING%20RECOMMENDER%20SYSTEM%20FOR%20INFREQUENTLY%20PURCHASED%20PRODUCT%20USING%20SLOPE-ONE%20ALGORITHM%20AND%20ASSOCIATION%20RULE%20MINING%20%2824%20pgs%29.pdf text en public http://eprints.utem.edu.my/id/eprint/15893/2/A%20collaborative%20filtering%20recommender%20system%20for%20infrequently%20purchased%20product%20using%20slope-one%20algorithm%20and%20association%20rule%20mining.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96238 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Information and Communication Technology Abdullah, Noraswaliza 1. Ahn, H.J.U.N., 2007. A Hybrid Collaborative Filtering Recommender System Using a New Similarity Measure. , pp.494–498. 2. 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