本文選題：通話記錄　切入點(diǎn)：局部社區(qū)發(fā)現(xiàn)　出處：《浙江大學(xué)》2017年碩士論文

【摘要】：我國大規(guī)模地普及移動電話和智能終端產(chǎn)生了海量的移動用戶歷史數(shù)據(jù),其中通話記錄能夠反映移動用戶在真實(shí)世界中的社會關(guān)系,在網(wǎng)絡(luò)里用戶的社交圈被稱為社區(qū),通過分析通話記錄發(fā)現(xiàn)移動用戶可能處于不同的社區(qū),比如有親友社區(qū)、工作社區(qū)和愛好社區(qū),不同的社區(qū)有不同的特征,這些特征被稱為社區(qū)畫像。本文根據(jù)通話記錄數(shù)據(jù)重點(diǎn)研究兩個問題,一是如何發(fā)現(xiàn)通話記錄中的社區(qū),二是如何為發(fā)現(xiàn)的社區(qū)構(gòu)建畫像。針對第一個問題,提出了基于邊權(quán)重的模塊度評測指標(biāo),和基于鄰集邊的局部社區(qū)發(fā)現(xiàn)算法。針對第二個問題,提出了構(gòu)建通話記錄網(wǎng)絡(luò)局部社區(qū)畫像的方法,另外為了從多角度了解用戶的通話特征和習(xí)慣,本文還提出了從多角度構(gòu)建局部社區(qū)畫像的框架。在公開數(shù)據(jù)集和通話記錄網(wǎng)絡(luò)上的測試結(jié)果驗(yàn)證了本文提出的局部社區(qū)發(fā)現(xiàn)算法的有效性,具體結(jié)果如下:(1)對有標(biāo)簽網(wǎng)絡(luò),該算法能夠發(fā)現(xiàn)比較完整的真實(shí)社區(qū);(2)對無標(biāo)簽網(wǎng)絡(luò),該算法發(fā)現(xiàn)的局部社區(qū)具有較高的模塊度。在通話記錄網(wǎng)絡(luò)上的測試結(jié)果表明,本文提出的多角度構(gòu)建局部社區(qū)畫像框架能夠有效地刻畫用戶的通話習(xí)慣和個人偏好。
[Abstract]:The extensive popularization of mobile phones and intelligent terminals in China has produced massive historical data of mobile users, in which phone records can reflect the social relations of mobile users in the real world, and the social circle of users in the network is called community.By analyzing the phone records, it is found that mobile users may be in different communities, such as communities with relatives and friends, working communities and loving communities, and different communities have different characteristics, which are called community portraits.According to the data of call record, this paper focuses on two problems, one is how to find the community in the call record, the other is how to construct the portrait of the community.In order to solve the first problem, an index of modular degree evaluation based on edge weight and a local community discovery algorithm based on adjacent set edge are proposed.To solve the second problem, a method of constructing local community portrait of call record network is put forward. In addition, in order to understand the characteristics and habits of users from multiple angles, this paper also proposes a framework for constructing local community portrait from multiple angles.The test results on the open data set and call record network verify the effectiveness of the local community discovery algorithm proposed in this paper. The results are as follows: 1) the tagged network.The algorithm can find a relatively complete real community with a high modularity to the untagged network and the local community found by the algorithm has a high degree of modularity.The test results on the call recording network show that the multi-angle local community portrait framework proposed in this paper can effectively describe the user's calling habits and personal preferences.
【學(xué)位授予單位】：浙江大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP301.6

【參考文獻(xiàn)】

相關(guān)期刊論文 前1條

1 吳英駿;黃翰;郝志峰;陳豐;;Local Community Detection Using Link Similarity[J];Journal of Computer Science & Technology;2012年06期

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本文編號：1717513