【摘要】：社交網(wǎng)絡(luò)的迅猛發(fā)展極大地方便了人們的日常生活、工作和學(xué)習(xí),但也帶來了大量復(fù)雜的交互行為和連接模式。如何有效地綜合分析網(wǎng)絡(luò)中的交互信息和網(wǎng)絡(luò)節(jié)點(diǎn)之間存在的連接信息,進(jìn)而完成高效的社團(tuán)檢測,是在當(dāng)前網(wǎng)絡(luò)多維屬性的復(fù)雜背景下進(jìn)行網(wǎng)絡(luò)分析所面臨的關(guān)鍵難題�；诖�,從有效融合兩類不同的異質(zhì)信息研究出發(fā),提出了一種基于交互行為和連接分析的社交網(wǎng)絡(luò)社團(tuán)檢測(CDUILS)方法。該方法基于兩類信息能夠從不同的角度反映網(wǎng)絡(luò)同一個社團(tuán)歸屬的假設(shè),采用聯(lián)合非負(fù)矩陣分解架構(gòu),以迭代更新的方式,同時利用兩類信息進(jìn)行社團(tuán)結(jié)果的獲取。在真實(shí)網(wǎng)絡(luò)數(shù)據(jù)集上的實(shí)驗(yàn)表明,與已有方法相比,所提方法能夠有效融合兩類信息進(jìn)行社團(tuán)檢測,取得了更好的社團(tuán)劃分質(zhì)量。
[Abstract]:The rapid development of social networks greatly facilitates people's daily life, work and study, but also brings a large number of complex interactive behavior and connection patterns. How to effectively analyze the interactive information in the network and the connection information between the network nodes, and then complete the efficient community detection, is the key problem in the network analysis under the complex background of the multi-dimensional attributes of the current network. Based on this, a social network community detection (CDUILS) method based on interaction behavior and connection analysis is proposed based on the effective fusion of two different kinds of heterogeneous information. Based on the assumption that the two kinds of information can reflect the same community belonging to the network from different angles, the joint non-negative matrix decomposition architecture is adopted to update the community results iteratively, and the two kinds of information are used to obtain the community results at the same time. The experiments on the real network data set show that compared with the existing methods, the proposed method can effectively fuse the two kinds of information for community detection, and obtain better community division quality.
【作者單位】： 國家數(shù)字交換系統(tǒng)工程技術(shù)研究中心;
【基金】：國家自然科學(xué)基金創(chuàng)新群體項(xiàng)目(61521003) 國家重點(diǎn)基礎(chǔ)研究發(fā)展計劃資助項(xiàng)目(2012CB315901,2012CB315905) 國家科技支撐計劃(2014BAH30B01)資助
【分類號】：TP393.09

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相關(guān)期刊論文 前2條

1 常振超;陳鴻昶;劉陽;于洪濤;黃瑞陽;;基于聯(lián)合矩陣分解的節(jié)點(diǎn)多屬性網(wǎng)絡(luò)社團(tuán)檢測[J];物理學(xué)報;2015年21期

2 許為;林柏鋼;林思娟;楊e，

本文編號：2506184