本文選題：電子商務(wù)　切入點：數(shù)據(jù)挖掘　出處：《伊犁師范學(xué)院》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：隨著互聯(lián)網(wǎng)技術(shù)的迅猛發(fā)展,很多傳統(tǒng)行業(yè)互聯(lián)網(wǎng)轉(zhuǎn)型,正逐漸發(fā)展為自建垂直化電子商務(wù)和平臺化電子商務(wù)經(jīng)營。網(wǎng)絡(luò)早已成為了人們購物很熟悉的途徑,絕大部分線下消費者逐漸變成了線上網(wǎng)購者。國家統(tǒng)計局統(tǒng)計數(shù)據(jù)顯示,11-14年中國社會消費品零售總額從18.4萬億上升至26.2萬億,平均年增長率在10%以上。這預(yù)示著中國零售市場發(fā)展環(huán)境好,16年數(shù)據(jù)有望突破30萬億。然而,這其中主要原因是電子商務(wù)在互聯(lián)網(wǎng)時代的得到了充分的拓展。各行各業(yè)根據(jù)傳統(tǒng)的商務(wù)場景互聯(lián)網(wǎng)化,將社會的資源分配趨于無明顯區(qū)域差別特點。目前平臺型電子商務(wù)平臺已不能優(yōu)質(zhì)地支撐起越來越多行業(yè)運營和龐大的經(jīng)濟體量,很多傳統(tǒng)企業(yè)發(fā)展垂直化電商,以更為專業(yè)和注重網(wǎng)絡(luò)用戶體驗為基準(zhǔn),以更為扁平化的管理銷售模式,提供更高質(zhì)量的網(wǎng)絡(luò)消費服務(wù)。本人在項目中的工作主要包括用戶行為數(shù)據(jù)指標(biāo)的定義,用戶行為數(shù)據(jù)的分析。通過對數(shù)據(jù)指標(biāo)的定義和前端用戶行為數(shù)據(jù)的采集,繼而訪問數(shù)據(jù)庫,采用數(shù)據(jù)挖掘的算法對數(shù)據(jù)的處理和分析,生成實時性可視化圖表。目前此項研究已經(jīng)在為聯(lián)通網(wǎng)上商城和手機商城等平臺提供用戶行為數(shù)據(jù)分析的支持,而且通過此項的數(shù)據(jù)研究已對產(chǎn)品設(shè)計產(chǎn)生了重要影響。
[Abstract]:With the rapid development of Internet technology, many traditional industries have been transformed into vertical e-commerce and platform e-commerce. The Internet has become a familiar way for people to shop. The vast majority of offline consumers are becoming online shoppers. Statistics from the National Bureau of Statistics show that retail sales of consumer goods in China rose from 18.4 trillion to 26.2 trillion in 11-14. The average annual growth rate is more than 10%. This indicates a good environment for China's retail market, with 16 years of data expected to exceed 30 trillion. The main reason for this is that e-commerce has been fully expanded in the Internet age. At present, the platform e-commerce platform can no longer support more and more industries operation and huge economic volume, and many traditional enterprises develop vertical e-commerce. To more professional and focus on the network user experience as a benchmark, with a more flat management sales model, to provide a higher quality of online consumer services. My work in the project mainly includes the definition of user behavior data indicators, User behavior data analysis. Through the definition of data indicators and front-end user behavior data collection, then access to the database, data mining algorithm for data processing and analysis, At present, this research has provided the support of user behavior data analysis for the platforms such as Unicom online shopping mall and mobile phone mall, and the data research has had an important impact on product design.
【學(xué)位授予單位】：伊犁師范學(xué)院
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2016
【分類號】：F724.6;F713.55;TP311.13
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本文編號：1607968