A Study of Using Text Mining Techniques to Predict the Stock

碩士 === 北臺灣科學技術學院 === 電子商務研究所 === 99 === Stock, futures and fund were popular's investment tool in Taiwan. How to gain profit efficiently is very important issue. It is difficult, since the Stock market is very complicated, dynamic and uncertainty. Now, there are so many papers to prove and anal...

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Bibliographic Details
Main Authors:	Ke,Yoshen, 柯禹伸
Other Authors:	Chen, Shang-rong
Format:	Others
Language:	zh-TW
Published:	2011
Online Access:	http://ndltd.ncl.edu.tw/handle/97412204302639146445

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spelling	ndltd-TW-099NTIS77630042015-10-13T20:08:44Z http://ndltd.ncl.edu.tw/handle/97412204302639146445 A Study of Using Text Mining Techniques to Predict the Stock 使用文字探勘技術預測股票漲跌之研究 Ke,Yoshen 柯禹伸碩士北臺灣科學技術學院電子商務研究所 99 Stock, futures and fund were popular's investment tool in Taiwan. How to gain profit efficiently is very important issue. It is difficult, since the Stock market is very complicated, dynamic and uncertainty. Now, there are so many papers to prove and analyze the relationship between basic phase and technology base for stock market. But, they didn’t consider any influence of news information yet. Today, investor can easy get the exchanged information from stock market by network. This study uses “text mining techniques” to analyze news paper. The key technologies : (1)China Word Segment System(CWSS)；(2) frequency of keyword-happened analysis；(3)text screening criteria were developed to find out keyword of stock trend and predict frequency of keyword-happened. Finally, we provide a new prediction model of stock trend, it can help investor to make a good decision. Chen, Shang-rong 陳尚蓉 2011 學位論文 ; thesis 78 zh-TW
collection	NDLTD
language	zh-TW
format	Others
sources	NDLTD
description	碩士 === 北臺灣科學技術學院 === 電子商務研究所 === 99 === Stock, futures and fund were popular's investment tool in Taiwan. How to gain profit efficiently is very important issue. It is difficult, since the Stock market is very complicated, dynamic and uncertainty. Now, there are so many papers to prove and analyze the relationship between basic phase and technology base for stock market. But, they didn’t consider any influence of news information yet. Today, investor can easy get the exchanged information from stock market by network. This study uses “text mining techniques” to analyze news paper. The key technologies : (1)China Word Segment System(CWSS)；(2) frequency of keyword-happened analysis；(3)text screening criteria were developed to find out keyword of stock trend and predict frequency of keyword-happened. Finally, we provide a new prediction model of stock trend, it can help investor to make a good decision.
author2	Chen, Shang-rong
author_facet	Chen, Shang-rong Ke,Yoshen 柯禹伸
author	Ke,Yoshen 柯禹伸
spellingShingle	Ke,Yoshen 柯禹伸 A Study of Using Text Mining Techniques to Predict the Stock
author_sort	Ke,Yoshen
title	A Study of Using Text Mining Techniques to Predict the Stock
title_short	A Study of Using Text Mining Techniques to Predict the Stock
title_full	A Study of Using Text Mining Techniques to Predict the Stock
title_fullStr	A Study of Using Text Mining Techniques to Predict the Stock
title_full_unstemmed	A Study of Using Text Mining Techniques to Predict the Stock
title_sort	study of using text mining techniques to predict the stock
publishDate	2011
url	http://ndltd.ncl.edu.tw/handle/97412204302639146445
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A Study of Using Text Mining Techniques to Predict the Stock

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