本文選題：重疊社區(qū) + 局部擴(kuò)張��； 參考：《小型微型計算機(jī)系統(tǒng)》2015年10期

【摘要】：重疊社區(qū)發(fā)現(xiàn)源于社交網(wǎng)絡(luò)、生物神經(jīng)網(wǎng)絡(luò)等復(fù)雜網(wǎng)絡(luò)結(jié)構(gòu)分析,在病毒傳播防范、網(wǎng)絡(luò)廣告投放和多跳自組路由協(xié)議設(shè)計等應(yīng)用中具有重要意義.現(xiàn)有重疊社區(qū)發(fā)現(xiàn)算法大都是基于靜態(tài)網(wǎng)絡(luò)的全局探測,面臨復(fù)雜度高、靈活性差和健壯性不足等諸多挑戰(zhàn).針對這些挑戰(zhàn),提出一種基于局部擴(kuò)張查詢的重疊社區(qū)發(fā)現(xiàn)算法—OCLEQ,首先以查詢的方式尋找包含特定點的k準(zhǔn)團(tuán)結(jié)構(gòu),然后基于團(tuán)結(jié)構(gòu)之間的鄰接性實現(xiàn)團(tuán)的快速擴(kuò)張,最后定義一個新的度量標(biāo)準(zhǔn)檢測和劃分遺漏點.仿真實驗結(jié)果表明,OCLEQ在重疊社區(qū)發(fā)現(xiàn)的效率和質(zhì)量上都優(yōu)于現(xiàn)有方法.
[Abstract]:The discovery of overlapping communities originates from the analysis of complex network structures such as social networks, biological neural networks and so on. It is of great significance in the application of virus transmission prevention, network advertising and multi-hop self-organizing routing protocol design. Most of the existing overlapping community discovery algorithms are based on the global detection of static networks, which face many challenges such as high complexity, poor flexibility and lack of robustness. To solve these challenges, an overlapping community discovery algorithm named -OCLEQ based on locally extended query is proposed. Firstly, the k-quasi structure with specific points is searched by query, and then the fast expansion of clusters is realized based on the adjacency between clusters. Finally, a new metric is defined to detect and divide the missing points. Simulation results show that OCLEQ is superior to existing methods in the efficiency and quality of overlapping community discovery.
【作者單位】： 燕山大學(xué)信息科學(xué)與工程學(xué)院;河北省計算機(jī)虛擬技術(shù)與系統(tǒng)集成重點實驗室;
【基金】：國家自然科學(xué)基金項目(61272466,61303233)資助 河北省自然科學(xué)基金項目(F2014203062)資助
【分類號】：O157.5;TP301.6
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本文編號：1916188