Online Clothing Shopbots via Web Content Extraction / Nurul Syazwani Ramzi

Ramzi, Nurul Syazwani (2017) Online Clothing Shopbots via Web Content Extraction / Nurul Syazwani Ramzi. Degree thesis, Universiti Teknologi MARA , Melaka.

[img] Text
TD_NURUL SYAZWANI RAMZI M CS 17_5.pdf

Download (0B)

Abstract

Online shopping has become a huge phenomenon lately. User or customer tends to compare the prices of homogeneous clothing category from different websites of online store before choosing and buying the item. User consumes a lot of time and money in order to compare the prices from multiple websites at one time manually since user needs to visit each of clothing websites. To solve this problem, online Clothing Shopbots via Web Content Extraction is developed so it can help user to reduce the time and money consumed to compare the prices because all the items and prices from multiple websites can be compared in just one website to ease the user or customer. Therefore, agile development methodology is very useful method to make the system successful and can be developed according to the schedule. An algorithm vision based page segmentation algorithm will be implemented in this system to extract the data from multiple websites and will be displayed in new website. By using this algorithm, the web page is segmented into several big blocks. These block tree is constructed by using DOM (document object model) tree. After that the data is searched using the nodes. A functionality testing is done to make sure the system meets the objectives. This system is useful for the user to make a right decision to buy a product without spending much money and time.

Item Type: Thesis (Degree)
Creators:
CreatorsEmail
Ramzi, Nurul SyazwaniUNSPECIFIED
Subjects: Q Science > QA Mathematics > Web-based user interfaces. User interfaces (Computer systems)
Divisions: Universiti Teknologi MARA, Melaka > Jasin Campus > Faculty of Computer and Mathematical Sciences
Item ID: 18940
Uncontrolled Keywords: Online shopping; Web Content Extraction; Algorithm
Last Modified: 29 Jan 2018 08:01
Depositing User: Perpustakaan UiTM Cawangan Melaka UiTM Cawangan Melaka
URI: http://ir.uitm.edu.my/id/eprint/18940

Actions (login required)

View Item View Item

Downloads

Downloads per month over past year