Web data cleaning and analytics for Malaysia tourism
This project is about data pre-processing, cleaning and analytics in Malaysia’s tourism sector. It will provide brief information about the importance of applying data analytics in tourism sector and some methodology on cleaning and pre-processing tourism dataset. To allow data analytics for some us...
| Main Author: | |
|---|---|
| Format: | Final Year Project / Dissertation / Thesis |
| Published: |
2019
|
| Subjects: | |
| Online Access: | http://eprints.utar.edu.my/3488/ http://eprints.utar.edu.my/3488/1/CS%2D2019%2D1503273.pdf |
| _version_ | 1848885914308182016 |
|---|---|
| author | Tee, Hong Le |
| author_facet | Tee, Hong Le |
| author_sort | Tee, Hong Le |
| building | UTAR Institutional Repository |
| collection | Online Access |
| description | This project is about data pre-processing, cleaning and analytics in Malaysia’s tourism sector. It will provide brief information about the importance of applying data analytics in tourism sector and some methodology on cleaning and pre-processing tourism dataset. To allow data analytics for some useful attributes, unwanted strings that lies in the attributes must be stripped away and only keep the numeric values which is the only value that brings the meaning of the attributes itself. New attributes are introduced which are integrated from the existing attributes such as Latitude, Longitude and text sentiment analysis scores. After that, data analytics phase is used to determine the tourism trends in Malaysia from multiple aspects such as particular tourism location, traveller’s country of origin and type of travellers which have different preferences. Data analytics that on time series of tourism trends will be discussed in this project too. |
| first_indexed | 2025-11-15T19:30:10Z |
| format | Final Year Project / Dissertation / Thesis |
| id | utar-3488 |
| institution | Universiti Tunku Abdul Rahman |
| institution_category | Local University |
| last_indexed | 2025-11-15T19:30:10Z |
| publishDate | 2019 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | utar-34882019-08-20T04:20:05Z Web data cleaning and analytics for Malaysia tourism Tee, Hong Le Q Science (General) This project is about data pre-processing, cleaning and analytics in Malaysia’s tourism sector. It will provide brief information about the importance of applying data analytics in tourism sector and some methodology on cleaning and pre-processing tourism dataset. To allow data analytics for some useful attributes, unwanted strings that lies in the attributes must be stripped away and only keep the numeric values which is the only value that brings the meaning of the attributes itself. New attributes are introduced which are integrated from the existing attributes such as Latitude, Longitude and text sentiment analysis scores. After that, data analytics phase is used to determine the tourism trends in Malaysia from multiple aspects such as particular tourism location, traveller’s country of origin and type of travellers which have different preferences. Data analytics that on time series of tourism trends will be discussed in this project too. 2019-04-23 Final Year Project / Dissertation / Thesis NonPeerReviewed application/pdf http://eprints.utar.edu.my/3488/1/CS%2D2019%2D1503273.pdf Tee, Hong Le (2019) Web data cleaning and analytics for Malaysia tourism. Final Year Project, UTAR. http://eprints.utar.edu.my/3488/ |
| spellingShingle | Q Science (General) Tee, Hong Le Web data cleaning and analytics for Malaysia tourism |
| title | Web data cleaning and analytics for Malaysia tourism |
| title_full | Web data cleaning and analytics for Malaysia tourism |
| title_fullStr | Web data cleaning and analytics for Malaysia tourism |
| title_full_unstemmed | Web data cleaning and analytics for Malaysia tourism |
| title_short | Web data cleaning and analytics for Malaysia tourism |
| title_sort | web data cleaning and analytics for malaysia tourism |
| topic | Q Science (General) |
| url | http://eprints.utar.edu.my/3488/ http://eprints.utar.edu.my/3488/1/CS%2D2019%2D1503273.pdf |