本文選題：核心網(wǎng) + 數(shù)據(jù)挖掘��； 參考：《北京郵電大學(xué)》2014年碩士論文

【摘要】：隨著移動(dòng)通信技術(shù)的飛速發(fā)展,移動(dòng)通信用戶規(guī)模不斷擴(kuò)大,運(yùn)營商的網(wǎng)絡(luò)建設(shè)也趨于成熟。在網(wǎng)絡(luò)運(yùn)行維護(hù)過程中,運(yùn)營商積累了海量的數(shù)據(jù),并且以指數(shù)級(jí)規(guī)模不斷增長。這些數(shù)據(jù),尤其是核心網(wǎng)的數(shù)據(jù)中,蘊(yùn)含著豐富的用戶行為信息。因此如何從這些大數(shù)據(jù)中快速并精準(zhǔn)地挖掘出對(duì)運(yùn)營商有價(jià)值的用戶行為信息,是運(yùn)營商普遍面臨的一個(gè)重要課題。在競(jìng)爭(zhēng)日趨激烈的通信運(yùn)營市場(chǎng)中,準(zhǔn)確掌握用戶行為信息對(duì)于運(yùn)營商來說有極其重要的意義。 本論文針對(duì)于核心網(wǎng)的多種數(shù)據(jù)源,提出了一套普適的數(shù)據(jù)挖掘流程,結(jié)合移動(dòng)通信用戶行為的特殊性,嘗試提出了一般的用戶行為分析方法,然后結(jié)合運(yùn)營商的現(xiàn)網(wǎng)采集數(shù)據(jù)進(jìn)行了實(shí)際的數(shù)據(jù)挖掘操作,并且對(duì)挖掘結(jié)果進(jìn)行了一系列的業(yè)務(wù)場(chǎng)景分析。 本論文的研究工作和成果如下： 1.基于核心網(wǎng)多種常見數(shù)據(jù)源的特點(diǎn),建立了專門針對(duì)核心網(wǎng)數(shù)據(jù)源的數(shù)據(jù)挖掘流程。 2.通過分析移動(dòng)通信用戶的一般行為特點(diǎn),提出了用戶行為分析的基本理論和方法。 3.基于現(xiàn)網(wǎng)的實(shí)際數(shù)據(jù),運(yùn)用聚類等一系列數(shù)據(jù)挖掘方法進(jìn)行數(shù)據(jù)挖掘的實(shí)現(xiàn)工作,得到了一系列有價(jià)值的用戶行為信息。 4.將己知的用戶行為在一定適用范圍內(nèi)進(jìn)行數(shù)值建模,并且深入研究了數(shù)值模型的實(shí)際含義。
[Abstract]:With the rapid development of mobile communication technology, the scale of mobile communication users continues to expand, and the network construction of operators tends to mature. In the process of network operation and maintenance, operators accumulate massive data and increase exponentially. These data, especially in the core network, contain rich user behavior information. Therefore, how to quickly and accurately mine the valuable user behavior information from these big data is an important topic that operators generally face. In the increasingly competitive communication operation market, it is very important for operators to accurately grasp user behavior information. In this paper, a set of universal data mining flow is proposed for multiple data sources in the core network. Combined with the particularity of mobile communication user behavior, a general user behavior analysis method is proposed. Then the actual data mining operation is carried out based on the data collected by the operator, and a series of business scenarios are analyzed. The research work and results of this thesis are as follows: 1. Based on the characteristics of many common data sources in the core network, a data mining process for the core network data sources is established. 2. By analyzing the general behavior characteristics of mobile communication users, the basic theory and method of user behavior analysis are put forward. 3. Based on the actual data of the present network, a series of data mining methods, such as clustering, are used to realize the data mining, and a series of valuable user behavior information are obtained. 4. The known user behavior is numerically modeled within a certain range of applications, and the actual meaning of the numerical model is studied in depth.
【學(xué)位授予單位】：北京郵電大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2014
【分類號(hào)】：TN929.5;TP311.13

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 徐前方;肖波;郭軍;;一種基于相關(guān)度統(tǒng)計(jì)的告警關(guān)聯(lián)規(guī)則挖掘算法[J];北京郵電大學(xué)學(xué)報(bào);2007年01期

2 郭少勇;芮蘭蘭;邱雪松;孟洛明;;基于用戶行為聚類的移動(dòng)終端業(yè)務(wù)故障檢測(cè)優(yōu)化機(jī)制[J];北京郵電大學(xué)學(xué)報(bào);2011年S1期

3 廖里,余英澤,吳渝,聶能;數(shù)據(jù)挖掘和數(shù)據(jù)倉庫及其在電信業(yè)中的應(yīng)用[J];重慶郵電學(xué)院學(xué)報(bào)(自然科學(xué)版);2000年04期

4 曲昭偉;鄭巖;呂廷杰;;基于聚類實(shí)現(xiàn)客戶行為分析[J];東北師大學(xué)報(bào)(自然科學(xué)版);2006年02期

5 唐才文;;WAP業(yè)務(wù)用戶行為模型分析[J];電腦知識(shí)與技術(shù);2008年27期

6 趙宏波 ,孟雅玲;數(shù)據(jù)挖掘在電信客戶關(guān)系管理中的應(yīng)用[J];電信技術(shù);2001年12期

7 呂巍,蔣波,陳潔;基于K-means算法的中國移動(dòng)市場(chǎng)顧客行為細(xì)分策略研究[J];管理學(xué)報(bào);2005年01期

8 張宏;方旭明;;移動(dòng)用戶行為及半時(shí)變計(jì)費(fèi)機(jī)制研究[J];電子與信息學(xué)報(bào);2013年04期

9 肖金玲;;大數(shù)據(jù)對(duì)通信行業(yè)帶來的影響[J];北方經(jīng)濟(jì);2013年18期

10 賈琳,李明;基于數(shù)據(jù)挖掘的電信客戶流失模型的建立與實(shí)現(xiàn)[J];計(jì)算機(jī)工程與應(yīng)用;2004年04期

，

本文編號(hào)：1934572