本文選題：社會(huì)網(wǎng)絡(luò) + 影響力最大化��； 參考：《計(jì)算機(jī)應(yīng)用研究》2016年12期

【摘要】：為了解決現(xiàn)有的影響力最大化研究沒(méi)有充分考慮主題對(duì)影響力節(jié)點(diǎn)挖掘的影響而導(dǎo)致特定主題下節(jié)點(diǎn)集合的影響范圍不大這一問(wèn)題,提出了一種社會(huì)網(wǎng)絡(luò)中基于主題的影響力最大化算法TIM。該算法首先根據(jù)主題敏感閾值對(duì)初始節(jié)點(diǎn)集進(jìn)行預(yù)處理,剔除干擾節(jié)點(diǎn),再在新的節(jié)點(diǎn)集合上分兩個(gè)階段進(jìn)行節(jié)點(diǎn)挖掘。第一階段挖掘主題權(quán)威性大的節(jié)點(diǎn),第二階段挖掘主題影響增量最大的節(jié)點(diǎn),最后綜合兩個(gè)階段的節(jié)點(diǎn)作為結(jié)果集并進(jìn)行實(shí)驗(yàn)驗(yàn)證。實(shí)驗(yàn)結(jié)果表明,相比其他算法,TIM算法挖掘的節(jié)點(diǎn)集合在特定主題下的影響范圍更大,時(shí)間復(fù)雜度更低。
[Abstract]:In order to solve the problem that the influence of topic on impact node mining is not fully taken into account in the existing research of maximizing influence, the influence scope of node set under a specific topic is not large. A topic based influence maximization algorithm, TIMI, is proposed in this paper. The algorithm preprocesses the initial node set according to the subject-sensitive threshold, removes the interference nodes, and then mine the nodes in two stages on the new node set. In the first stage, the most authoritative nodes are mined. In the second stage, the nodes with the largest increment are mined. Finally, the nodes of the two stages are synthesized as the result set and verified by experiments. The experimental results show that compared with other algorithms, the node set mined by Tim algorithm has a larger influence range and lower time complexity under a specific topic.
【作者單位】： 江蘇大學(xué)計(jì)算機(jī)科學(xué)與通信工程學(xué)院;大全集團(tuán);
【基金】：國(guó)家自然科學(xué)基金資助項(xiàng)目(71271117) 江蘇省科技支撐計(jì)劃資助項(xiàng)目(BE2011156)
【分類(lèi)號(hào)】：TP393.09;G206
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本文編號(hào)：1814241