本文關(guān)鍵詞：證券領(lǐng)域個(gè)性化推薦平臺(tái)　出處：《電子科技大學(xué)》2014年碩士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 大眾推薦 個(gè)性化推薦 推薦算法 基于用戶行為 基于文本分析

【摘要】：證券是我國(guó)金融行業(yè)的一個(gè)重要領(lǐng)域,它不僅關(guān)系到我國(guó)市場(chǎng)化的進(jìn)展,還關(guān)系到企業(yè)改制的順利進(jìn)行,但是,隨著股票發(fā)行的核準(zhǔn)制度、證券交易浮動(dòng)的傭金制度、強(qiáng)化上市公司的信息披露、證券對(duì)國(guó)際市場(chǎng)的逐步開(kāi)發(fā)、大力推行證券投資基金等措施的實(shí)施,證券領(lǐng)域從過(guò)去的壟斷暴利行業(yè)轉(zhuǎn)化成如今的開(kāi)發(fā)競(jìng)爭(zhēng)性的微利行業(yè),證券領(lǐng)域的發(fā)展受到了嚴(yán)峻的挑戰(zhàn)。在這種嚴(yán)峻的挑戰(zhàn)下,證券營(yíng)銷(xiāo)就變得空前的重要,隨著信息技術(shù)的高速發(fā)展與應(yīng)用,利用信息化技術(shù)來(lái)解決證券營(yíng)銷(xiāo)問(wèn)題已經(jīng)成為當(dāng)前的一個(gè)研究熱點(diǎn)。本文力圖從信息化技術(shù)理論和實(shí)際出發(fā),提出一種證券領(lǐng)域的個(gè)性化推薦框架平臺(tái)和兩種新的證券營(yíng)銷(xiāo)策略。在證券領(lǐng)域,隨著證券業(yè)務(wù)的飛速發(fā)展、證券產(chǎn)品的類(lèi)型越來(lái)越多和證券客戶歷史交易信息的急劇增長(zhǎng),用戶需要花費(fèi)大量的時(shí)間與精力才能找到自己所需要的信息,這種瀏覽大量無(wú)關(guān)信息的過(guò)程無(wú)疑會(huì)使淹沒(méi)在信息過(guò)載問(wèn)題中的用戶不斷流失,給證券公司帶來(lái)惡劣的后果,在這種情況下,證券營(yíng)銷(xiāo)的推薦需求特別是個(gè)性化推薦的要求越來(lái)越強(qiáng)烈。為了改善證券領(lǐng)域中傳統(tǒng)的大眾(無(wú)差別)推薦,本文提出了一種證券領(lǐng)域的個(gè)性化推薦框架平臺(tái)和兩種更為有效的個(gè)性化推薦設(shè)計(jì)方法。(1)針對(duì)證券信息的個(gè)性化推薦平臺(tái):本推薦平臺(tái)將系統(tǒng)分成13個(gè)獨(dú)立且相互聯(lián)系的子模塊,各模塊之間通過(guò)相互調(diào)用來(lái)完成最終的推薦任務(wù),還給出了相應(yīng)的數(shù)據(jù)流及應(yīng)急設(shè)計(jì)的方案。(2)基于用戶行為的個(gè)性化推薦方法:通過(guò)分析用戶在股票、理財(cái)產(chǎn)品、資訊等證券信息的瀏覽、購(gòu)買(mǎi)、訂閱等行為,設(shè)計(jì)并實(shí)現(xiàn)個(gè)性化推薦列表,并從真實(shí)數(shù)據(jù)的實(shí)驗(yàn)結(jié)果中可以看出此推薦方法是有效的。(3)基于文本分析的個(gè)性化推薦方法:在證券領(lǐng)域有很多信息都是以文本的形式存在,然而它們卻有著非比尋常的意義,基于文本分析的個(gè)性化推薦方法充分的利用文本內(nèi)容的天然優(yōu)勢(shì)為用戶提供個(gè)性化的推薦列表,此方法也可很好的解決行為推薦方法中的冷啟動(dòng)問(wèn)題,并真實(shí)數(shù)據(jù)的實(shí)驗(yàn)結(jié)果中可以看出此推薦方法是有效的。
[Abstract]:Security is an important component of China's financial industry, it is not only related to the progress of our country market, but also related to enterprise restructuring smoothly, however, as the stock issuance approval system, the securities and Exchange Commission floating system, strengthen information disclosure of listed companies, securities development gradually to the international market, the implementation of vigorously promote the securities investment fund and other measures, the field of securities conversion from the past monopoly profiteering industry development competition of today's low profit industry, development of securities market has been a severe challenge. In this challenge, the securities marketing becomes ever more important, with the rapid development of information technology and Application, to solve the the problem of securities marketing and use of information technology has become a research hotspot. This paper starts from the theory and practice of information technology, put forward a kind of personalized domain security The recommended framework platform and two new types of securities marketing strategy. In the field of securities, along with the rapid development of the securities business, the rapid growth of securities products more and more types and securities customer transaction information, users need to spend a lot of time and effort to find the information they need, the process of browsing a large number of irrelevant information will undoubtedly the submerged in the problem of information overload in continual loss of customers, to bring bad consequences to the securities company, in this case, the recommended demand of securities marketing especially more and more strong requirements of personalized recommendation. In order to improve the traditional public securities in the field (no difference) recommendation, this paper proposes a personalized stock field the recommended framework platform and two kind of more effective personalized recommendation method. (1) according to the securities information recommendation platform: this recommendation platform system is divided into 13 independent and interrelated sub modules, each tune used to complete the final recommended tasks through among modules, data flow and the corresponding emergency design scheme is given. (2) the personalized recommendation method based on user behavior: through the analysis of the user in the stock, financial products, information and other securities information browsing. The purchase, subscription and other acts, the design and implementation of personalized recommendation list, and experimental results from real data can be seen in the recommended method is effective. (3) the personalized recommendation method based on text analysis: in the field of securities have a lot of information are in the form of text, but they are of great significance the use of the natural advantages of text content, text analysis and personalized recommendation method provide personalized recommendation list for users based on this method can resolve the behavior of good recommendation method in cold start The problem, and the experimental results of real data, can be seen that this recommendation method is effective.

【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：F832.51;TP391.3

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