本文選題：菜品拉動力　切入點(diǎn)：復(fù)雜網(wǎng)絡(luò)　出處：《北京交通大學(xué)》2017年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著餐飲業(yè)經(jīng)營逐漸互聯(lián)網(wǎng)化及餐飲云服務(wù)技術(shù)的發(fā)展,一些擁有相對完善信息管理系統(tǒng)的餐飲商家和服務(wù)商積累下大量餐飲交易數(shù)據(jù)。從餐飲交易數(shù)據(jù)中挖掘有效信息,對精準(zhǔn)營銷、銷售風(fēng)險評估等具有重大意義。但現(xiàn)有方法在餐飲歷史數(shù)據(jù)信息挖掘時存在精度低、適用性差等系列問題。為從餐飲交易數(shù)據(jù)中準(zhǔn)確挖掘有效信息,本文致力于以復(fù)雜網(wǎng)絡(luò)理論為基礎(chǔ),提出基于菜品復(fù)雜網(wǎng)絡(luò)的餐飲數(shù)據(jù)分析方法。在餐飲領(lǐng)域,菜品的拉動力反映了菜品因自身消費(fèi)增長而拉動其他菜品整體消費(fèi)增長的能力。本文從餐飲交易數(shù)據(jù)出發(fā),利用復(fù)雜網(wǎng)絡(luò)相關(guān)理論,通過計算和分析菜品拉動力,進(jìn)行有效信息挖掘。為了實(shí)現(xiàn)上述目標(biāo),本文首先分析并量化了餐飲交易數(shù)據(jù)中菜品間作用關(guān)系,通過與隨機(jī)網(wǎng)絡(luò)模型比較構(gòu)建了一種符號菜品復(fù)雜網(wǎng)絡(luò),可以對菜品間的拉動關(guān)系和阻礙關(guān)系進(jìn)行定性和定量計算�；诜柌似肪W(wǎng)絡(luò),本文進(jìn)一步利用復(fù)雜網(wǎng)絡(luò)傳播模型的思想結(jié)合餐飲數(shù)據(jù)特點(diǎn)提出了一種菜品拉動力計算方法。由于餐飲數(shù)據(jù)中菜品關(guān)系的特殊性,現(xiàn)有網(wǎng)絡(luò)傳播模型無法充分反映菜品間關(guān)系。本文針對符號網(wǎng)絡(luò)的特點(diǎn),通過改變數(shù)據(jù)判斷條件,提出了一種符號網(wǎng)絡(luò)下的線性閾值模型,并將其應(yīng)用于菜品拉動力的計算當(dāng)中。在上述工作的基礎(chǔ)上,本文在某餐飲公司提供的真實(shí)賬單數(shù)據(jù)上進(jìn)行了實(shí)驗(yàn),并分別將本文所提方法與餐飲業(yè)常用的菜品排序方法以及一種符號網(wǎng)絡(luò)上的節(jié)點(diǎn)排序方法進(jìn)行了比較和分析,驗(yàn)證了本文方法的合理性和有效性。
[Abstract]:With the development of catering business and the development of catering cloud service technology, some catering merchants and service providers with relatively perfect information management system have accumulated a large amount of catering transaction data. It is of great significance for precision marketing and sales risk assessment. However, the existing methods have some problems such as low precision and poor applicability in the mining of catering historical data. Based on the theory of complex network, this paper puts forward a method of food data analysis based on complex network of dishes. The pulling power of dishes reflects the ability of the whole consumption of other dishes to increase because of their own consumption growth. Based on the catering transaction data, this paper makes use of the theory of complex network to calculate and analyze the pulling power of dishes. In order to achieve the above objectives, this paper first analyzes and quantifies the relationship between the dishes in the catering transaction data, and constructs a complex network of symbolic dishes by comparing with the stochastic network model. Qualitative and quantitative calculations of pull and drag relationships between dishes can be made. Based on the symbolic dishes network, Based on the idea of complex network communication model and the characteristics of catering data, this paper puts forward a method to calculate the pulling power of food. Because of the particularity of the relationship between food and beverage, The existing network propagation model can not fully reflect the relationship between dishes. In this paper, according to the characteristics of symbol network, a linear threshold model based on symbol network is proposed by changing the data judgment condition. On the basis of the above work, this paper has carried on the experiment on the real bill data provided by a catering company. The method proposed in this paper is compared and analyzed with the common food ordering method and a node sorting method on the symbol network. The rationality and effectiveness of the proposed method are verified.
【學(xué)位授予單位】：北京交通大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：O157.5

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