本文選題：樸素貝葉斯模型　切入點(diǎn)：移動(dòng)用戶職業(yè)　出處：《內(nèi)蒙古大學(xué)》2013年碩士論文

【摘要】：隨著移動(dòng)通信、互聯(lián)網(wǎng)業(yè)務(wù)的迅速發(fā)展。手機(jī)已經(jīng)從奢侈品變成了生活日用品,是我們?nèi)粘Ｉ钪胁豢扇鄙俚囊徊糠�。人們隨時(shí)隨地使用手機(jī)打電話、發(fā)短信、上網(wǎng),而用戶的這些行為以及其個(gè)人基本信息均在運(yùn)營(yíng)商處有所記錄。如何能夠通過(guò)流量費(fèi)、通話費(fèi)、短信條數(shù)、上網(wǎng)時(shí)長(zhǎng)四個(gè)加權(quán)因素來(lái)綜合刻畫(huà)用戶職業(yè)類型。對(duì)于整體運(yùn)營(yíng)商行業(yè)來(lái)說(shuō),是極其重要和有價(jià)值的研究課題。 對(duì)特定人群提供特定服務(wù)和合適的資費(fèi)尤為重要。因?yàn)椴煌穆殬I(yè)有不同的消費(fèi)傾向和消費(fèi)能力,對(duì)選擇資費(fèi)和話費(fèi)業(yè)務(wù)上有很大的不同。所以通過(guò)用戶以往數(shù)據(jù),歸納出不同職業(yè)用戶的特征,再對(duì)未知職業(yè)的用戶做出預(yù)測(cè),對(duì)公司市場(chǎng)和業(yè)務(wù)流程有很大的幫助,可以節(jié)約大量不必要的推廣成本,提高推廣轉(zhuǎn)化率。 我們運(yùn)用樸素貝葉斯模型先對(duì)信息完整的用戶職業(yè)信息進(jìn)行分類。以職場(chǎng)新人為例,根據(jù)刻畫(huà)職場(chǎng)新人的四個(gè)影響因素與職場(chǎng)新人職業(yè)之間的關(guān)系。預(yù)測(cè)出兩個(gè)職業(yè)信息不詳?shù)穆殘?chǎng)新人分別是從事房地產(chǎn)經(jīng)營(yíng)產(chǎn)業(yè)和其他商務(wù)服務(wù)業(yè)的。我們將數(shù)據(jù)表中手機(jī)信息不詳?shù)穆殘?chǎng)新人單獨(dú)列舉出來(lái),根據(jù)上問(wèn)中信息完整的職場(chǎng)新人的相關(guān)指標(biāo)因子來(lái)確定手機(jī)信息不詳?shù)穆殘?chǎng)新人終端大致的價(jià)格范圍。當(dāng)職場(chǎng)新人與聚類中心的距離小的時(shí)候,這個(gè)職場(chǎng)新人就屬于這個(gè)類別。當(dāng)這個(gè)距離大的時(shí)候,該職場(chǎng)新人就不屬于這個(gè)類別。
[Abstract]:With the rapid development of mobile communication and Internet business, mobile phone has changed from luxury to daily necessities, which is an indispensable part of our daily life. And the user's behavior and their personal basic information are recorded at the operator's office. How can they be recorded through traffic charges, phone calls, text messages, It is an extremely important and valuable research topic for the whole operator industry to describe the occupation types of users synthetically by the four weighted factors of the length of the Internet. It is particularly important to provide specific services and appropriate rates to specific groups of people. Because different occupations have different propensity and ability to consume, they are very different in selecting tariff and telephone services. The characteristics of different professional users are summed up, and then the users of unknown occupations are predicted, which is of great help to the market and business process of the company, which can save a lot of unnecessary promotion costs and increase the extension conversion rate. We use naive Bayes model to classify the occupational information of users with complete information. According to the relationship between the four factors that affect the new career and the occupation of the new workplace, we predict that the two new professionals with unknown information are engaged in the real estate business and other business services respectively. We will count. According to the list of new workplace workers whose mobile phone information is not available, According to the relevant index factors of the newlyweds with complete information in the above question, to determine the approximate price range of the new workplace newcomers with unknown mobile phone information. When the distance between the workplace newlyweds and the cluster center is small, This new worker falls into this category. When the distance is large, the new worker does not fall into this category.
【學(xué)位授予單位】：內(nèi)蒙古大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2013
【分類號(hào)】：TP311.13

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