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研究生:鍾文荃
研究生(外文):Wen-Chiuan Chung
論文名稱:新聞語意特徵擷取流程設計與股價變化關聯性分析
論文名稱(外文):News semantic feature extraction process design and the correlation analysis between news and stock price
指導教授:洪炯宗
指導教授(外文):Jorng-Tzong Horng
學位類別:碩士
校院名稱:國立中央大學
系所名稱:資訊工程學系
學門:工程學門
學類:電資工程學類
論文出版年:2016
畢業學年度:104
語文別:中文
論文頁數:31
中文關鍵詞:文本探勘股票關聯性分析
外文關鍵詞:text miningstockcorrelation analysis
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近年來,有許多的研究希望透過市場上現有的消息,例如公司的財務報表以及新聞報導,來進行對股價的預測及走向判斷。根據Fama提出的效率市場假說[12],這些公開的訊息會反映在股價的變化上,因此,如何從這些訊息中擷取出有效的內容以判別股價的走向是此類研究的重點。然而在這一方面,過往的研究大多以詞袋(Bag of words)來進行模型的建立,再進一步則是使用複合詞(complex words)如N-gram、名詞短語(Noun phrase)等等。較少有研究進一步的在文中去搜尋與股價有確切關聯的內容。在本研究中,我們使用了不同的文本探勘工具去找尋與特定公司更具有關聯性的內容,並分析這些內容與其股價的關係。我們希望透過應用近年來不斷成熟的文本探勘技術,針對新聞中單詞的詞性、句子的結構以及情感分數進行更有效的特徵擷取,以增進預測模型的精準度。
In recent years, there are many studies try to predict the direction of stock price with available message on the market, such as financial statements and financial news. According to Fama's efficient market hypothesis[12], these public information will be reflected in the change of stock price. Therefore, how to retrieve the effective message from news to determine the stock price trend is the significant point of such research. However, in this aspect, past studies mostly established prediction model with bag of words, still further was the use of complex word such as n-gram, noun phrase, etc, few studies have further to search the text content associated with the stock price in the news. In this study, we used some text mining tools to find the more relevant content of specific company and analyze the relationship between these content and the company’s stock price. We hope to get effective features through applied the more mature text mining technology for part of speech of words, sentence structure and sentiment analysis, we can enhance the accuracy of the prediction model.
摘要 i
ABSTRACT ii
Table of Contents iii
List of Tables iv
List of Figures v
Chapter 1 Introduction 1
Chapter 2 Related Works 2
Chapter 3 Materials and Methods 4
3.1 Data source 4
3.2 Work flow 5
3.3 Preprocessing 6
3.4 Multi-layer feature extraction 7
3.5 Semantic abstraction 11
3.6 Feature selection and representation 11
3.7 Training and classification 12
Chapter 4 Results 13
Chapter 5 Discussion and Conclusion 17
References 19
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12. Fama, Eugene F. "The behavior of stock-market prices." The journal of Business 38.1 (1965): 34-105.
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24. Groth, Sven S., and Jan Muntermann. "An intraday market risk management approach based on textual analysis." Decision Support Systems 50.4 (2011): 680-691.
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