Collaborative recommender system for online jewelry store
The existence of vast amount of data exist in internet nowadays has become a dilemma in the field of electronic commerce. Searching of the desired information has become so inconvenient since there are too many irrelevant information exist all over the shopping platform. One of the most popular s...
| Main Author: | |
|---|---|
| Format: | Final Year Project Report / IMRAD |
| Language: | English |
| Published: |
Universiti Malaysia Sarawak, (UNIMAS)
2015
|
| Subjects: | |
| Online Access: | http://ir.unimas.my/id/eprint/12194/ http://ir.unimas.my/id/eprint/12194/3/Morris%20Hon.pdf |
| _version_ | 1848837146405765120 |
|---|---|
| author | Hon, Morris Mao Ning |
| author_facet | Hon, Morris Mao Ning |
| author_sort | Hon, Morris Mao Ning |
| building | UNIMAS Institutional Repository |
| collection | Online Access |
| description | The existence of vast amount of data exist in internet nowadays has become a
dilemma in the field of electronic commerce. Searching of the desired information has
become so inconvenient since there are too many irrelevant information exist all over the
shopping platform. One of the most popular solution nowadays to solve this dilemma is
recommender system. Recommender systems are now pervasive in user’s lives. They aim to
help users in finding items that they would like to buy or consider based on huge amount of
data collected. Parsing a huge amount of data to predict user’s preference base on his or her
similarity with other group of users is the core of recommender system. One of the famous
approach that could be applied to the implementation of recommender system is collaborative
filtering approach. The motivation to do this project comes from my eagerness to improve my
web developing skill especially in the field of jewelry e-commerce and to get a deep
understanding of recommender system. In this project, a prototype of online jewelry selling
store with the implementation of a collaborative filtering based recommender system was
developed. The algorithm under collaborative filtering approach that been used in this project
is called slope one algorithm which basically works by predicting user’s preference based on
other user’s rating history on specific items in the system. Finally, the prototype built in this
project was evaluated in term of the performance of the recommender system under user’s
point of view and the results of evaluation was discussed in details to draw out a conclusion
for its further improvement. |
| first_indexed | 2025-11-15T06:35:01Z |
| format | Final Year Project Report / IMRAD |
| id | unimas-12194 |
| institution | Universiti Malaysia Sarawak |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T06:35:01Z |
| publishDate | 2015 |
| publisher | Universiti Malaysia Sarawak, (UNIMAS) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | unimas-121942023-10-10T08:20:19Z http://ir.unimas.my/id/eprint/12194/ Collaborative recommender system for online jewelry store Hon, Morris Mao Ning H Social Sciences (General) HF Commerce T Technology (General) The existence of vast amount of data exist in internet nowadays has become a dilemma in the field of electronic commerce. Searching of the desired information has become so inconvenient since there are too many irrelevant information exist all over the shopping platform. One of the most popular solution nowadays to solve this dilemma is recommender system. Recommender systems are now pervasive in user’s lives. They aim to help users in finding items that they would like to buy or consider based on huge amount of data collected. Parsing a huge amount of data to predict user’s preference base on his or her similarity with other group of users is the core of recommender system. One of the famous approach that could be applied to the implementation of recommender system is collaborative filtering approach. The motivation to do this project comes from my eagerness to improve my web developing skill especially in the field of jewelry e-commerce and to get a deep understanding of recommender system. In this project, a prototype of online jewelry selling store with the implementation of a collaborative filtering based recommender system was developed. The algorithm under collaborative filtering approach that been used in this project is called slope one algorithm which basically works by predicting user’s preference based on other user’s rating history on specific items in the system. Finally, the prototype built in this project was evaluated in term of the performance of the recommender system under user’s point of view and the results of evaluation was discussed in details to draw out a conclusion for its further improvement. Universiti Malaysia Sarawak, (UNIMAS) 2015 Final Year Project Report / IMRAD NonPeerReviewed text en http://ir.unimas.my/id/eprint/12194/3/Morris%20Hon.pdf Hon, Morris Mao Ning (2015) Collaborative recommender system for online jewelry store. [Final Year Project Report / IMRAD] (Unpublished) |
| spellingShingle | H Social Sciences (General) HF Commerce T Technology (General) Hon, Morris Mao Ning Collaborative recommender system for online jewelry store |
| title | Collaborative recommender system for online jewelry store |
| title_full | Collaborative recommender system for online jewelry store |
| title_fullStr | Collaborative recommender system for online jewelry store |
| title_full_unstemmed | Collaborative recommender system for online jewelry store |
| title_short | Collaborative recommender system for online jewelry store |
| title_sort | collaborative recommender system for online jewelry store |
| topic | H Social Sciences (General) HF Commerce T Technology (General) |
| url | http://ir.unimas.my/id/eprint/12194/ http://ir.unimas.my/id/eprint/12194/3/Morris%20Hon.pdf |