頂點(diǎn)帶屬性網(wǎng)絡(luò)鏈接預(yù)測(cè)的參數(shù)選擇方法
發(fā)布時(shí)間：2018-12-19 09:42
【摘要】：鏈接預(yù)測(cè)問(wèn)題在社會(huì)學(xué)、人類學(xué)、信息科學(xué)以及計(jì)算機(jī)科學(xué)等各個(gè)領(lǐng)域都受到了廣泛的關(guān)注.在基于相似度的鏈接預(yù)測(cè)的方法中,Katz指標(biāo)是一種重要的頂點(diǎn)相似度指標(biāo).鑒于Katz指標(biāo)中參數(shù)的可選擇性,提出了一種基于參數(shù)選擇的頂點(diǎn)帶屬性網(wǎng)絡(luò)的鏈接預(yù)測(cè)算法.Katz相似度指標(biāo)是基于路徑相似性鏈接預(yù)測(cè)結(jié)果評(píng)價(jià)指標(biāo),Katz相似度指標(biāo)中參數(shù)的取值會(huì)直接影響到Katz指標(biāo)預(yù)測(cè)的結(jié)果.由于頂點(diǎn)帶屬性網(wǎng)絡(luò)含屬性和拓?fù)潆p重信息,算法思想是結(jié)合頂點(diǎn)屬性信息進(jìn)行參數(shù)選擇,可以通過(guò)調(diào)節(jié)Katz相似度指標(biāo)中參數(shù)的值,使Katz相似度盡可能和屬性相似度靠近,將頂點(diǎn)屬性相似度信息融入Katz相似度之中,以期達(dá)到屬性信息和結(jié)構(gòu)信息的有機(jī)融合.實(shí)驗(yàn)結(jié)果證明了該算法可以得到較高質(zhì)量的預(yù)測(cè)結(jié)果.
[Abstract]:Link prediction has received wide attention in sociology, anthropology, information science and computer science. In the method of link prediction based on similarity, Katz index is an important index of vertex similarity. In view of the selectivity of the parameters in the Katz index, a link prediction algorithm based on the vertex and attribute network based on parameter selection is proposed. The Katz similarity index is an evaluation index based on the path similarity link prediction results. The value of parameters in Katz similarity index will directly affect the prediction result of Katz index. Because the vertex with attribute network contains attribute and topology information, the idea of the algorithm is to select the parameters by combining the vertex attribute information. The Katz similarity can be as close as possible to the attribute similarity by adjusting the value of the parameters in the Katz similarity index. The vertex attribute similarity information is integrated into Katz similarity in order to achieve the organic fusion of attribute information and structure information. The experimental results show that the algorithm can get high quality prediction results.
【作者單位】： 揚(yáng)州大學(xué)信息工程學(xué)院;南京大學(xué)軟件新技術(shù)國(guó)家重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(61379066,61379064,61472344,61402395)資助 江蘇省自然科學(xué)基金項(xiàng)目(BK20130452,BK2012672,BK2012128,BK20140492)資助 江蘇省教育廳自然科學(xué)基金項(xiàng)目(12KJB520019,13KJB520026)資助 江蘇省六大人才高峰項(xiàng)目(2011-DZXX-032)資助
【分類號(hào)】：O157.5
本文編號(hào)：2386748
[Abstract]:Link prediction has received wide attention in sociology, anthropology, information science and computer science. In the method of link prediction based on similarity, Katz index is an important index of vertex similarity. In view of the selectivity of the parameters in the Katz index, a link prediction algorithm based on the vertex and attribute network based on parameter selection is proposed. The Katz similarity index is an evaluation index based on the path similarity link prediction results. The value of parameters in Katz similarity index will directly affect the prediction result of Katz index. Because the vertex with attribute network contains attribute and topology information, the idea of the algorithm is to select the parameters by combining the vertex attribute information. The Katz similarity can be as close as possible to the attribute similarity by adjusting the value of the parameters in the Katz similarity index. The vertex attribute similarity information is integrated into Katz similarity in order to achieve the organic fusion of attribute information and structure information. The experimental results show that the algorithm can get high quality prediction results.
【作者單位】： 揚(yáng)州大學(xué)信息工程學(xué)院;南京大學(xué)軟件新技術(shù)國(guó)家重點(diǎn)實(shí)驗(yàn)室;
【基金】：國(guó)家自然科學(xué)基金項(xiàng)目(61379066,61379064,61472344,61402395)資助 江蘇省自然科學(xué)基金項(xiàng)目(BK20130452,BK2012672,BK2012128,BK20140492)資助 江蘇省教育廳自然科學(xué)基金項(xiàng)目(12KJB520019,13KJB520026)資助 江蘇省六大人才高峰項(xiàng)目(2011-DZXX-032)資助
【分類號(hào)】：O157.5
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1 肖熙;于寶海;;對(duì)《SCDD》優(yōu)化法參數(shù)選擇的探討[J];上海交通大學(xué)學(xué)報(bào);1982年01期
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