發(fā)布時(shí)間：2018-03-23 20:26

  本文選題：可拓學(xué)　切入點(diǎn)：策略生成　出處：《廣東工業(yè)大學(xué)》2013年碩士論文

【摘要】：隨著社會(huì)經(jīng)濟(jì)全球化發(fā)展,企業(yè)競(jìng)爭(zhēng)由產(chǎn)品競(jìng)爭(zhēng)轉(zhuǎn)向市場(chǎng)競(jìng)爭(zhēng),市場(chǎng)競(jìng)爭(zhēng)的關(guān)鍵在于爭(zhēng)奪客戶資源,如今,客戶已經(jīng)成為企業(yè)生存發(fā)展的重要資源。為了維持企業(yè)的長(zhǎng)期發(fā)展,增加企業(yè)的核心競(jìng)爭(zhēng)力和提高企業(yè)的利潤(rùn),很多企業(yè)管理者都越來(lái)越重視客戶關(guān)系的管理和客戶的價(jià)值的提高。此外,客戶關(guān)系理論也越來(lái)越受到研究者的重視,許多國(guó)內(nèi)外學(xué)者對(duì)客戶關(guān)系和客戶價(jià)值進(jìn)行了長(zhǎng)期的研究,并將研究的成果成功應(yīng)用到商業(yè)領(lǐng)域。本文通過(guò)對(duì)客戶價(jià)值理論的了解、利用決策樹(shù)技術(shù)和可拓學(xué)方法理論分析設(shè)計(jì)了提高客戶價(jià)值的可拓策略生成系統(tǒng),從理論上和實(shí)踐上探索了決策樹(shù)技術(shù)在策略生成系統(tǒng)的應(yīng)用問(wèn)題,為以后的研究提供了基礎(chǔ)和方向。 在目前的可拓策略生成系統(tǒng)的方法中,一般都是先建立矛盾問(wèn)題的可拓模型,然后通過(guò)關(guān)聯(lián)函數(shù)分析,建立問(wèn)題庫(kù)和策略庫(kù),在策略生成階段,采用菱形思維方法生成策略,即先用發(fā)散思維對(duì)矛盾問(wèn)題的相關(guān)樹(shù)進(jìn)行可拓變換,然后采用收斂的思維方法對(duì)生成的策略進(jìn)行評(píng)價(jià),推薦優(yōu)度高的策略供決策者選擇。這種方法難以對(duì)矛盾問(wèn)題的核心問(wèn)題進(jìn)行分析,生成的策略針對(duì)性不強(qiáng)。本文探討性地利用本體知識(shí)和決策樹(shù)技術(shù)共同建立本體知識(shí)拓展分析樹(shù),通過(guò)本體知識(shí)拓展分析樹(shù)挖掘解決矛盾問(wèn)題的可拓知識(shí)和矛盾問(wèn)題的核心問(wèn)題,采用對(duì)核心問(wèn)題可拓變換的方法生成策略,這種方法提高了可拓策略生成系統(tǒng)的智能性和策略生成的準(zhǔn)確性。 本文首先介紹了客戶價(jià)值理論、決策樹(shù)、本體知識(shí)和可拓策略生成的相關(guān)知識(shí)；其次,探討了提高客戶價(jià)值可拓模型的建立、本體知識(shí)拓展分析樹(shù)模型的建立過(guò)程,研究了本體知識(shí)拓展分析樹(shù)在可拓策略生成中的應(yīng)用問(wèn)題,即通過(guò)分析本體知識(shí)拓展分析樹(shù)的特征,挖掘客戶價(jià)值的可拓知識(shí)和矛盾問(wèn)題的核心問(wèn)題；再次,介紹了提高客戶價(jià)值的可拓策略生成步驟和生成的結(jié)果；最后,總結(jié)了本文的創(chuàng)新點(diǎn)和未來(lái)努力的方向。 本文的創(chuàng)新之處： (1)本文結(jié)合本體知識(shí)、決策樹(shù)技術(shù)和客戶價(jià)值的理論,提出了本體知識(shí)拓展分析樹(shù)概念,給出了本體知識(shí)拓展分析樹(shù)模型的構(gòu)建過(guò)程,以及通過(guò)本體知識(shí)拓展分析樹(shù)建立目標(biāo)與條件的核問(wèn)題的過(guò)程。 (2)本文探討了本體知識(shí)拓展分析樹(shù)在可拓策略生成系統(tǒng)的應(yīng)用研究。通過(guò)對(duì)本體知識(shí)拓展分析樹(shù)分析,獲得相關(guān)領(lǐng)域的可拓知識(shí),有效找到矛盾問(wèn)題的核心問(wèn)題,并且對(duì)相關(guān)條件進(jìn)行可拓變換,生成有效的策略供決策者選擇。 (3)本文根據(jù)客戶價(jià)值的可拓知識(shí)和核心問(wèn)題,提出了提高客戶價(jià)值的可拓策略生成步驟,探索了策略生成的新模式。 本文是廣東省自然科學(xué)基金資助項(xiàng)目(批準(zhǔn)號(hào)：10151009001000044)—“基于可拓?cái)?shù)據(jù)挖掘的客戶價(jià)值研究”的研究成果。
[Abstract]:With the development of social and economic globalization, enterprise competition changes from product competition to market competition. The key of market competition is to compete for customer resources. Nowadays, customer has become an important resource for enterprise survival and development. To increase the core competitiveness of enterprises and improve the profits of enterprises, many enterprise managers pay more and more attention to the management of customer relationship and the improvement of customer value. In addition, the theory of customer relationship is paid more and more attention by researchers. Many scholars at home and abroad have carried out long-term research on customer relationship and customer value, and successfully applied the research results to the field of business. Based on the theory of decision tree technology and extension method, an extension strategy generation system is designed to improve customer value. The application of decision tree technology in policy generation system is explored theoretically and practically. It provides the basis and direction for the future research. In the present extension strategy generation system, the extension model of contradiction problem is established first, and then the problem base and strategy database are established by the correlation function analysis. In the strategy generation stage, the rhombic thinking method is used to generate the strategy. That is, using divergent thinking to transform the related tree of the contradiction problem, and then using the convergent thinking method to evaluate the generated strategy. Recommend strategies with high degree of excellence for decision makers. This method is difficult to analyze the core problems of contradictory problems. In this paper, ontology knowledge and decision tree technology are used to build ontology knowledge extension and analysis tree. The extension tree of ontology knowledge is used to mine the extension knowledge and the core problem of the contradiction problem, and the method of extension transformation of the core problem is adopted to generate the strategy. This method improves the intelligence and accuracy of extension policy generation system. This paper first introduces the theory of customer value, decision tree, ontology knowledge and extension strategy generation related knowledge, secondly, discusses the establishment of extension model for improving customer value, the process of building ontology knowledge extension analysis tree model. This paper studies the application of ontology knowledge extension analysis tree in extension strategy generation, that is, mining the core problem of customer value extension knowledge and contradiction by analyzing the characteristics of ontology knowledge expansion analysis tree. This paper introduces the generating steps and results of the extension strategy to improve customer value, and finally, summarizes the innovation points and the direction of future efforts in this paper. The innovations of this paper are as follows:. 1) based on the theory of ontology knowledge, decision tree technology and customer value, the concept of ontology knowledge extension analysis tree is put forward, and the process of constructing ontology knowledge expansion analysis tree model is given. And the process of establishing the kernel problem of target and condition through ontology knowledge extension and analysis tree. In this paper, the application of ontology knowledge extension analysis tree in extension strategy generation system is discussed. Through the analysis of ontology knowledge extension analysis tree, the extension knowledge in related fields is obtained, and the core problem of contradiction problem is found effectively. The extension transformation of the relevant conditions is carried out to generate effective strategies for decision makers to choose. 3) according to the extension knowledge and core problems of customer value, this paper puts forward the steps of generating extension strategy to improve customer value, and probes into a new model of policy generation. This paper is the research result of the project supported by Guangdong Natural Science Foundation (Grant No.: 10151009001000044- "customer value Research based on Extensible data Mining").
【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)】：TP391.1

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