本文選題：社交網(wǎng)絡(luò)　切入點(diǎn)：關(guān)系強(qiáng)度　出處：《北京郵電大學(xué)》2014年碩士論文　論文類型：學(xué)位論文

【摘要】：目前如Facebook、微博等在線社交網(wǎng)絡(luò)服務(wù)(Online Social Network, OSN)已經(jīng)成為互聯(lián)網(wǎng)中的重要應(yīng)用,用戶數(shù)持續(xù)增長,成為很多人必不可缺的信息獲取手段和社交途徑。 用戶及其之間的連接關(guān)系是組成和維持社交網(wǎng)絡(luò)的基本要素,本文以連接關(guān)系為研究對(duì)象,從連接強(qiáng)度、連接類型、連接動(dòng)態(tài)性等角度對(duì)其進(jìn)行深入研究。這一研究也可以為OSN領(lǐng)域的相關(guān)研究提供理論基礎(chǔ),如推薦系統(tǒng)、隱私保護(hù)等問題,幫助服務(wù)提供商提供更具有實(shí)際價(jià)值的服務(wù)。 本文首先針對(duì)連接關(guān)系,調(diào)研了多個(gè)領(lǐng)域中的研究理論和成果,對(duì)其進(jìn)行對(duì)比和分類,提出了基于OSN的用戶連接關(guān)系研究的內(nèi)容框架。隨后,分別提出了基于多元逐步回歸的連接強(qiáng)度測量算法(MSLR)和基于隨機(jī)游走策略的連接類型識(shí)別算法(RW-RT),能夠充分利用社交網(wǎng)絡(luò)中的用戶信息、交互信息和用戶之間的依賴于好友關(guān)系形成的拓?fù)渚W(wǎng)絡(luò),準(zhǔn)確的識(shí)別用戶之間的關(guān)系強(qiáng)度和關(guān)系類型。利用新浪微博的中的真實(shí)用戶數(shù)據(jù),關(guān)系強(qiáng)度測量MSLR的準(zhǔn)確度約為80%,連接類型算法RW-RT的測量準(zhǔn)確度約為85%。證明了算法的有效性和準(zhǔn)確性。對(duì)于用戶連接關(guān)系的動(dòng)態(tài)性問題,由于用戶行為會(huì)導(dǎo)致用戶關(guān)系隨時(shí)間發(fā)生變化,因此本文從用戶行為的時(shí)間模式為出發(fā)點(diǎn),側(cè)面反映連接關(guān)系的動(dòng)態(tài)性。利用小波變換和動(dòng)態(tài)時(shí)間彎曲的K-Medoids算法(WT-DKM),得到微博用戶行為的典型時(shí)間模式。 此外,本文還基于MSLR算法和RW-RT算法開發(fā)了一款新浪微博應(yīng)用,能夠自動(dòng)測量用戶之間的關(guān)系強(qiáng)度,并從好友分組的角度幫助用戶自動(dòng)管理自己的好友關(guān)系,證明了算法的實(shí)際價(jià)值。
[Abstract]:At present, online Social Network (OSNs), such as Facebook and Weibo, has become an important application in the Internet, and the number of users has continued to grow, and it has become an indispensable means of obtaining information and social networking for many people. The connection relationship between users and their connections is the basic element to form and maintain the social network. In this paper, the connection relationship is taken as the research object, from the connection strength, the connection type, This research can also provide a theoretical basis for the related research in the field of OSN, such as recommendation system, privacy protection and so on, and help service providers to provide more valuable services. In this paper, firstly, according to the connection relation, the research theories and achievements in many fields are investigated, compared and classified, and the content framework of the user connection relationship research based on OSN is put forward. The connection strength measurement algorithm based on multiple stepwise regression (MSLR) and the connection type recognition algorithm based on random walk strategy (RW-RTP) are proposed respectively, which can make full use of user information in social networks. Interactive information and the topological network between users that depend on the friend relationship, accurately identify the relationship between the user and the relationship between the intensity and type of relationship, using Sina Weibo in the real user data, The accuracy of relational strength measurement MSLR is about 80, the accuracy of connection type algorithm RW-RT is about 850.The validity and accuracy of the algorithm are proved. Since user behavior can cause user relationships to change over time, this paper starts with the time pattern of user behavior. By using wavelet transform and dynamic time bending K-Medoids algorithm WT-DKMN, the typical time pattern of Weibo's user behavior is obtained. In addition, this paper also developed a Sina Weibo application based on MSLR algorithm and RW-RT algorithm, which can automatically measure the relationship between users and help users manage their friends automatically from the point of view of friend grouping. The practical value of the algorithm is proved.
【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)】：TP393.09

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本文編號(hào)：1637179