基于可拓?cái)?shù)據(jù)挖掘的客戶價(jià)值分析軟件設(shè)計(jì)與實(shí)現(xiàn)
發(fā)布時(shí)間：2018-07-15 19:34
【摘要】：隨著信息技術(shù)和“以客戶為中心”的經(jīng)營(yíng)模式發(fā)展,客戶價(jià)值逐漸成為客戶關(guān)系管理(CRM)的核心;科學(xué)、全面地掌握和評(píng)估客戶價(jià)值大小并采取有效的、正確的策略提升客戶價(jià)值,成為企業(yè)有效管理客戶資源和把握市場(chǎng)的關(guān)鍵。因此,有效的客戶價(jià)值管理和營(yíng)銷策略對(duì)企業(yè)的發(fā)展具有十分重要的意義。利用數(shù)據(jù)挖掘技術(shù)處理海量的客戶數(shù)據(jù),根據(jù)客戶價(jià)值理論對(duì)客戶進(jìn)行細(xì)分、客戶流失預(yù)測(cè)等是客戶價(jià)值領(lǐng)域研究的熱點(diǎn)技術(shù)。由于現(xiàn)有的數(shù)據(jù)挖掘技術(shù)更多的是從靜態(tài)數(shù)據(jù)中獲取靜態(tài)知識(shí),忽略了變換對(duì)數(shù)據(jù)影響作用,故基于數(shù)據(jù)挖掘的客戶價(jià)值分析系統(tǒng)不能挖掘變換作用的知識(shí)及變換導(dǎo)致客戶價(jià)值變化的規(guī)律。然而,這些變換知識(shí)對(duì)幫助企業(yè)解決客戶價(jià)值矛盾問題具有指導(dǎo)意義。 本文提出將可拓學(xué)和可拓?cái)?shù)據(jù)挖掘技術(shù)應(yīng)用到客戶價(jià)值分析中,研究設(shè)計(jì)與實(shí)現(xiàn)一種基于可拓?cái)?shù)據(jù)挖掘的客戶價(jià)值分析軟件,用于挖掘客戶價(jià)值變換的知識(shí),為企業(yè)掌握各種營(yíng)銷變換下客戶價(jià)值變化規(guī)律和衡量營(yíng)銷策略優(yōu)劣提供方便、可靠的工具。 本文主要完成了以下研究工作： 1.研究客戶價(jià)值理論知識(shí),客戶價(jià)值評(píng)價(jià)特征選取方法,并設(shè)計(jì)與實(shí)現(xiàn)了具備適用性、靈活性的客戶價(jià)值評(píng)價(jià)體系。 2.介紹了可拓學(xué)和可拓?cái)?shù)據(jù)挖掘理論知識(shí),信息元形式化表示客戶信息及可拓?cái)?shù)據(jù)挖掘過程。 3.研究了客戶價(jià)值各要素的關(guān)聯(lián)函數(shù)和綜合關(guān)聯(lián)函數(shù)模型構(gòu)造方法,提取發(fā)生傳導(dǎo)變換的傳導(dǎo)特征方法,及獲取客戶價(jià)值可拓知識(shí)的技術(shù)規(guī)則與算法設(shè)計(jì)。 4.對(duì)JFreechart可視化圖表技術(shù)進(jìn)行研究,實(shí)現(xiàn)了圖形化展示客戶價(jià)值分析結(jié)果。 5.詳細(xì)設(shè)計(jì)了基于可拓?cái)?shù)據(jù)挖掘的客戶價(jià)值分析軟件架構(gòu)、軟件功能模塊劃分,通過采取動(dòng)態(tài)庫(kù)和數(shù)據(jù)轉(zhuǎn)換服務(wù)以屏蔽底層數(shù)據(jù),從信息元特征中提取客戶價(jià)值評(píng)價(jià)指標(biāo),分析企業(yè)客戶價(jià)值情況,實(shí)現(xiàn)了客戶價(jià)值可拓分類知識(shí)、傳導(dǎo)知識(shí)獲取及挖掘結(jié)果可視化顯示。 最后,以某服裝企業(yè)的應(yīng)用為例,研究該企業(yè)的客戶價(jià)值可拓分類知識(shí)和傳導(dǎo)知識(shí)的挖掘,表明獲取的知識(shí)對(duì)企業(yè)調(diào)整營(yíng)銷策略、采取差異化服務(wù)具有很大的參考價(jià)值。 本文創(chuàng)新之處在于： 1.將可拓?cái)?shù)據(jù)挖掘技術(shù)應(yīng)用于客戶價(jià)值分析中,設(shè)計(jì)實(shí)現(xiàn)基于可拓?cái)?shù)據(jù)挖掘的客戶價(jià)值分析軟件,幫助企業(yè)解決衡量策略作用規(guī)律和優(yōu)劣,動(dòng)態(tài)地掌握客戶價(jià)值變化情況,彌補(bǔ)了當(dāng)時(shí)基于傳統(tǒng)數(shù)據(jù)挖掘的客戶價(jià)值系統(tǒng)不能挖掘變換知識(shí)的不足,為客戶價(jià)值系統(tǒng)提供新的解決思路。 2.現(xiàn)有的可拓?cái)?shù)據(jù)挖掘軟件或系統(tǒng)往往采用的是單一固定形式的關(guān)聯(lián)函數(shù)模型,而本文實(shí)現(xiàn)了三種基本的關(guān)聯(lián)函數(shù)模型,并由需求選擇具體的模型;通過建立動(dòng)態(tài)表,數(shù)據(jù)轉(zhuǎn)換和動(dòng)態(tài)建立評(píng)價(jià)體系,動(dòng)態(tài)識(shí)別傳導(dǎo)特征能夠適用于不同企業(yè)進(jìn)行可拓分類知識(shí)和傳導(dǎo)知識(shí)挖掘,具有更強(qiáng)的通用性和靈活性。 本文是廣東省自然科學(xué)基金資助項(xiàng)目“基于可拓?cái)?shù)據(jù)挖掘的客戶價(jià)值研究”(批準(zhǔn)號(hào)：10151009001000044)的研究成果。
[Abstract]:With the development of information technology and "customer centered" management model, customer value has gradually become the core of customer relationship management (CRM); scientific, comprehensive grasp and evaluation of the value of customer value, and take effective and correct strategies to improve customer value, become the key to the effective management of customer resources and the market. Effective customer value management and marketing strategy are of great significance to the development of the enterprise. Using data mining technology to deal with mass customer data, subdividing customers according to customer value theory, prediction of customer loss and so on is a hot technology in the field of customer value research. The state data acquires static knowledge and ignores the influence of transformation on data. Therefore, the customer value analysis system based on data mining can not excavate the knowledge of transformation and change the law of customer value change. However, these transformation knowledge is of guiding significance to help enterprises to solve the contradiction of customer value.
This paper puts forward the application of extenics and extension data mining to customer value analysis, and studies the design and implementation of a customer value analysis software based on extension data mining, which is used to excavate the knowledge of customer value transformation, and for the enterprise to master the change rule of customer value and measure the marketing strategy under various marketing changes. It is a reliable tool.
This paper mainly completed the following research work:
1. study customer value theory knowledge, customer value evaluation feature selection method, and design and implement a customer value evaluation system with applicability and flexibility.
2. introduced extenics and extension data mining theory knowledge, information element formalized customer information and extension data mining process.
3. the related function of each factor of customer value and the construction method of the integrated association function model are studied. The method of conducting the conduction characteristic of the conduction transformation is extracted and the technical rules and algorithms for obtaining the extension knowledge of customer value are designed.
4. research on JFreechart visualization chart technology, and achieve graphical display of customer value analysis results.
5. the architecture of customer value analysis software based on extension data mining is designed in detail, and the software function module is divided. By adopting dynamic library and data conversion service to shield the underlying data, extracting customer value evaluation index from information element characteristics, analyzing customer value situation, realizing customer value extension classification knowledge and conducting knowledge. The visual display of the acquisition and mining results.
Finally, taking the application of a garment enterprise as an example, this paper studies the enterprise's customer value extension classification knowledge and the transmission knowledge mining. It shows that the acquired knowledge is of great reference value to the enterprise adjustment marketing strategy and the differential service.
The innovation of this article lies in:
1. apply the extension data mining technology to the customer value analysis, design and implement the customer value analysis software based on the extension data mining, help the enterprise to solve the law and the good and bad of the measurement strategy, and dynamically grasp the change of the customer value, and make up for the knowledge that the customer value system based on the traditional data mining can not be excavated. Lack of knowledge provides a new solution for customer value system.
2. the existing extension data mining software or system often uses a single fixed form of association function model, and this paper implements three basic association function models, and selects specific models from demand. By establishing dynamic tables, data conversion and dynamic establishment of evaluation system, dynamic identification of transmission features can be applied to different enterprises. The extension knowledge and knowledge mining are more versatile and flexible.
This paper is the research achievement of the Guangdong Provincial Natural Science Foundation Project "customer value research based on extension data mining" (approval number: 10151009001000044).
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP311.13
本文編號(hào)：2125154
[Abstract]:With the development of information technology and "customer centered" management model, customer value has gradually become the core of customer relationship management (CRM); scientific, comprehensive grasp and evaluation of the value of customer value, and take effective and correct strategies to improve customer value, become the key to the effective management of customer resources and the market. Effective customer value management and marketing strategy are of great significance to the development of the enterprise. Using data mining technology to deal with mass customer data, subdividing customers according to customer value theory, prediction of customer loss and so on is a hot technology in the field of customer value research. The state data acquires static knowledge and ignores the influence of transformation on data. Therefore, the customer value analysis system based on data mining can not excavate the knowledge of transformation and change the law of customer value change. However, these transformation knowledge is of guiding significance to help enterprises to solve the contradiction of customer value.
This paper puts forward the application of extenics and extension data mining to customer value analysis, and studies the design and implementation of a customer value analysis software based on extension data mining, which is used to excavate the knowledge of customer value transformation, and for the enterprise to master the change rule of customer value and measure the marketing strategy under various marketing changes. It is a reliable tool.
This paper mainly completed the following research work:
1. study customer value theory knowledge, customer value evaluation feature selection method, and design and implement a customer value evaluation system with applicability and flexibility.
2. introduced extenics and extension data mining theory knowledge, information element formalized customer information and extension data mining process.
3. the related function of each factor of customer value and the construction method of the integrated association function model are studied. The method of conducting the conduction characteristic of the conduction transformation is extracted and the technical rules and algorithms for obtaining the extension knowledge of customer value are designed.
4. research on JFreechart visualization chart technology, and achieve graphical display of customer value analysis results.
5. the architecture of customer value analysis software based on extension data mining is designed in detail, and the software function module is divided. By adopting dynamic library and data conversion service to shield the underlying data, extracting customer value evaluation index from information element characteristics, analyzing customer value situation, realizing customer value extension classification knowledge and conducting knowledge. The visual display of the acquisition and mining results.
Finally, taking the application of a garment enterprise as an example, this paper studies the enterprise's customer value extension classification knowledge and the transmission knowledge mining. It shows that the acquired knowledge is of great reference value to the enterprise adjustment marketing strategy and the differential service.
The innovation of this article lies in:
1. apply the extension data mining technology to the customer value analysis, design and implement the customer value analysis software based on the extension data mining, help the enterprise to solve the law and the good and bad of the measurement strategy, and dynamically grasp the change of the customer value, and make up for the knowledge that the customer value system based on the traditional data mining can not be excavated. Lack of knowledge provides a new solution for customer value system.
2. the existing extension data mining software or system often uses a single fixed form of association function model, and this paper implements three basic association function models, and selects specific models from demand. By establishing dynamic tables, data conversion and dynamic establishment of evaluation system, dynamic identification of transmission features can be applied to different enterprises. The extension knowledge and knowledge mining are more versatile and flexible.
This paper is the research achievement of the Guangdong Provincial Natural Science Foundation Project "customer value research based on extension data mining" (approval number: 10151009001000044).
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP311.13
【參考文獻(xiàn)】
相關(guān)期刊論文 前7條
1 陳文偉;;挖掘變化知識(shí)的可拓?cái)?shù)據(jù)挖掘研究[J];中國(guó)工程科學(xué);2006年11期
2 任永功;王政軍;;基于JSP和MySQL的動(dòng)態(tài)表結(jié)構(gòu)的設(shè)計(jì)與實(shí)現(xiàn)[J];計(jì)算機(jī)工程;2006年05期
3 權(quán)明富,齊佳音,舒華英;客戶價(jià)值評(píng)價(jià)指標(biāo)體系設(shè)計(jì)[J];南開管理評(píng)論;2004年03期
4 楊春燕,張擁軍,蔡文;可拓集合及其應(yīng)用研究[J];數(shù)學(xué)的實(shí)踐與認(rèn)識(shí);2002年02期
5 蔡文;可拓學(xué)概述[J];系統(tǒng)工程理論與實(shí)踐;1998年01期
6 王秀義;基于JDBC的數(shù)據(jù)庫(kù)連接池及實(shí)現(xiàn)[J];計(jì)算機(jī)系統(tǒng)應(yīng)用;2005年04期
7 菅志剛,金旭;數(shù)據(jù)挖掘中數(shù)據(jù)預(yù)處理的研究與實(shí)現(xiàn)[J];計(jì)算機(jī)應(yīng)用研究;2004年07期
相關(guān)碩士學(xué)位論文 前1條
1 陳遠(yuǎn)高;基于數(shù)據(jù)挖掘的客戶價(jià)值管理研究[D];浙江大學(xué);2002年
，本文編號(hào)：2125154
本文鏈接：http://www.sikaile.net/guanlilunwen/kehuguanxiguanli/2125154.html
最近更新
教材專著
