本文選題：數(shù)據(jù)挖掘　切入點：手機沖浪　出處：《河北科技大學》2013年碩士論文　論文類型：學位論文

【摘要】：隨著科技的不斷發(fā)展，互聯(lián)網(wǎng)已經(jīng)成為人們?nèi)粘Ｉ�、工作和學習中不可或缺的一部分。面對海量的各種互聯(lián)網(wǎng)信息，我們往往很難精準定位自己所需要的內(nèi)容。手機訪問互聯(lián)網(wǎng)已經(jīng)逐漸與人們的日常生活緊密連接在一起，為了更好的服務于手機客戶，手機沖浪應運而生，以最便捷的低門檻方式為客戶提供完善的互聯(lián)網(wǎng)適配訪問體驗，手機沖浪可以分揀海量的互聯(lián)網(wǎng)信息，，幫助客戶快速精準定位所需的內(nèi)容。 手機沖浪是通過短信、彩信、WAP等形式，為您提供手機網(wǎng)址導航、資訊聚合、個性訂閱、網(wǎng)頁加速等服務的業(yè)務，其中的子產(chǎn)品沖浪助手每天通過彩信或者短信方式將互聯(lián)網(wǎng)信息發(fā)送給訂購客戶，客戶點擊便可閱讀詳細內(nèi)容。訂購客戶也可以進行個性化訂閱設置，添加感興趣的互聯(lián)網(wǎng)信息。本課題正是通過研究沖浪助手，根據(jù)平臺反饋的信息數(shù)據(jù)，挖掘分析用戶的行為習慣，對客戶進行不同維度的劃分，針對不同客戶下發(fā)信息，能很好的提高提升點擊率。 本文主要介紹了數(shù)據(jù)挖掘的理論基礎知識、關(guān)聯(lián)模型、分類模型和客戶關(guān)系模型，通過與對手機沖浪業(yè)務相結(jié)合，進行數(shù)據(jù)采集、并對數(shù)據(jù)進行清洗的方式，利用分類和關(guān)聯(lián)進行計算和挖掘，而進行內(nèi)容偏好分析、標簽關(guān)聯(lián)分析，從而形成客戶-內(nèi)容-業(yè)務三維矩陣的構(gòu)建，從而建立最終的四個模型。通過本文驗證，手機沖浪利用分類和關(guān)聯(lián)是一種行之有效的方法，可見本文能夠有效地預測和關(guān)聯(lián)用戶，具有實際的應用價值。
[Abstract]:With the development of science and technology, the Internet has become an indispensable part of people's daily life, work and study. We often find it difficult to pinpoint what we need. Mobile phone access to the Internet has become more and more closely connected to people's daily lives. In order to better serve mobile phone customers, mobile phone surfing has emerged. With the most convenient low-threshold way to provide customers with a perfect Internet adaptation access experience, mobile phone surfing can sort out a huge amount of Internet information, to help customers quickly and accurately locate the content needed. Mobile phone surfing is through SMS, MMS WAP and other forms to provide you with mobile site navigation, information aggregation, personality subscription, web page acceleration and other services. One of the sub-product surfing assistants sends Internet information to the ordering customer through MMS or SMS every day, and the customer can read the details by clicking. The ordering customer can also make personalized subscription settings. Add interesting Internet information. This topic is through the study of surfing assistants, according to the platform feedback information data, mining and analysis of user behavior habits, customers are divided into different dimensions, for different customers to send information, Can improve the click rate very well. This paper mainly introduces the basic theory of data mining, association model, classification model and customer relationship model, through the combination of mobile phone surfing business, data collection, and data cleaning way, Classification and association are used to compute and mine, and content preference analysis and label association analysis are carried out to form the three dimensional matrix of customer-content-business, and the final four models are established. The classification and association of mobile phone surfing is an effective method. It can be seen that this paper can effectively predict and associate users and has practical application value.
【學位授予單位】：河北科技大學
【學位級別】：碩士
【學位授予年份】：2013
【分類號】：TP311.13

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本文編號：1631276