Applying Data Mining to Analyze Online Auction Market
碩士 === 朝陽科技大學 === 工業工程與管理系碩士班 === 91 === The online shopping is getting popular in Taiwan. According to NetValue latest report, the user online shopping are getting more and more, average there is 15 percentage on growth every season, and online shopping have been accept by most of generations. Th...
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Others |
Language: | zh-TW |
Published: |
2003
|
Online Access: | http://ndltd.ncl.edu.tw/handle/62504796784389536078 |
id |
ndltd-TW-091CYUT5031013 |
---|---|
record_format |
oai_dc |
spelling |
ndltd-TW-091CYUT50310132015-10-13T16:56:51Z http://ndltd.ncl.edu.tw/handle/62504796784389536078 Applying Data Mining to Analyze Online Auction Market 應用資料採礦分析線上拍賣市場之模式 Zhi-Xiong Hunag 黃志雄 碩士 朝陽科技大學 工業工程與管理系碩士班 91 The online shopping is getting popular in Taiwan. According to NetValue latest report, the user online shopping are getting more and more, average there is 15 percentage on growth every season, and online shopping have been accept by most of generations. The research send three major issues. First, we study clustering online user’s profiles. Secondly, classified by the different classification method. Applied can reach different results or not. Finally, classification and comparison results used to construct a final-price prediction mode. The ebay website data is used by K-Means cluster statistic method and SOM(Self-Organization Map) neural network to categorize according to 8 parameters. The classification results are used predict the price by BPN(Back-Propagation Network) neural network model. Chu-Chai Chan 詹智強 2003 學位論文 ; thesis 116 zh-TW |
collection |
NDLTD |
language |
zh-TW |
format |
Others
|
sources |
NDLTD |
description |
碩士 === 朝陽科技大學 === 工業工程與管理系碩士班 === 91 === The online shopping is getting popular in Taiwan. According to NetValue latest report, the user online shopping are getting more and more, average there is 15 percentage on growth every season, and online shopping have been accept by most of generations.
The research send three major issues. First, we study clustering online user’s profiles. Secondly, classified by the different classification method. Applied can reach different results or not. Finally, classification and comparison results used to construct a final-price prediction mode. The ebay website data is used by K-Means cluster statistic method and SOM(Self-Organization Map) neural network to categorize according to 8 parameters. The classification results are used predict the price by BPN(Back-Propagation Network) neural network model.
|
author2 |
Chu-Chai Chan |
author_facet |
Chu-Chai Chan Zhi-Xiong Hunag 黃志雄 |
author |
Zhi-Xiong Hunag 黃志雄 |
spellingShingle |
Zhi-Xiong Hunag 黃志雄 Applying Data Mining to Analyze Online Auction Market |
author_sort |
Zhi-Xiong Hunag |
title |
Applying Data Mining to Analyze Online Auction Market |
title_short |
Applying Data Mining to Analyze Online Auction Market |
title_full |
Applying Data Mining to Analyze Online Auction Market |
title_fullStr |
Applying Data Mining to Analyze Online Auction Market |
title_full_unstemmed |
Applying Data Mining to Analyze Online Auction Market |
title_sort |
applying data mining to analyze online auction market |
publishDate |
2003 |
url |
http://ndltd.ncl.edu.tw/handle/62504796784389536078 |
work_keys_str_mv |
AT zhixionghunag applyingdataminingtoanalyzeonlineauctionmarket AT huángzhìxióng applyingdataminingtoanalyzeonlineauctionmarket AT zhixionghunag yīngyòngzīliàocǎikuàngfēnxīxiànshàngpāimàishìchǎngzhīmóshì AT huángzhìxióng yīngyòngzīliàocǎikuàngfēnxīxiànshàngpāimàishìchǎngzhīmóshì |
_version_ |
1717777610471112704 |