本文選題：馬氏鏈 + PageRank算法��； 參考：《華中師范大學(xué)》2017年碩士論文

【摘要】：近年來(lái),對(duì)研究對(duì)象的分類問(wèn)題已經(jīng)在多個(gè)研究領(lǐng)域得到了廣泛的應(yīng)用,分類的方法也得到了巨大的發(fā)展,如聚類分析、KNN算法、決策樹、支持向量機(jī)等等。本文以研究實(shí)際通訊數(shù)據(jù)的社群分類問(wèn)題出發(fā),提出了一種PageRank算法和SimRank算法相結(jié)合的新的分類方法。在兩個(gè)實(shí)際案例中得到實(shí)踐,并將結(jié)果分別與真實(shí)情況和傳統(tǒng)聚類方法結(jié)果進(jìn)行了比較,整體效果和結(jié)果解釋均較為理想。本文提出的方法適用于研究任意對(duì)象與對(duì)象之間的關(guān)系。先將問(wèn)題轉(zhuǎn)化為一個(gè)簡(jiǎn)單而直觀的點(diǎn)邊結(jié)構(gòu)圖模型,通過(guò)PageRank算法計(jì)算狀態(tài)點(diǎn)在整個(gè)圖中的“重要性”,通過(guò)SimRank算法測(cè)量對(duì)象之間結(jié)構(gòu)上的相似性,根據(jù)它們與其他對(duì)象的關(guān)系,有效地進(jìn)行分類。本文的基本思想是“兩個(gè)對(duì)象是相似的,則與他們相關(guān)的對(duì)象應(yīng)相似�！北疚牡难芯靠梢砸暈闊o(wú)監(jiān)督學(xué)習(xí)(無(wú)指導(dǎo)學(xué)習(xí))的實(shí)踐和探索。
[Abstract]:In recent years, the classification of research objects has been widely used in many research fields, and the classification methods have been greatly developed, such as clustering analysis KNN algorithm, decision tree, support vector machine and so on. In this paper, we propose a new classification method which combines PageRank algorithm with SimRank algorithm. The results are compared with the real cases and the traditional clustering methods respectively. The overall effect and the interpretation of the results are satisfactory. The method proposed in this paper is suitable for studying the relationship between arbitrary objects and objects. Firstly, the problem is transformed into a simple and intuitionistic point-edge structure graph model. The importance of state points in the whole graph is calculated by PageRank algorithm, and the structural similarity between objects is measured by SimRank algorithm, according to their relationship with other objects. Classify effectively. The basic idea of this paper is that "if two objects are similar, the objects related to them should be similar." The research in this paper can be regarded as the practice and exploration of unsupervised learning (unsupervised learning).
【學(xué)位授予單位】：華中師范大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：C815

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