【摘要】：[目的/意義]從科研合作網(wǎng)絡(luò)"小世界現(xiàn)象"和"無標(biāo)度特性"出發(fā),對(duì)網(wǎng)絡(luò)中的未知鏈路產(chǎn)生連接的可能性進(jìn)行預(yù)測(cè)。[方法/過程]采用Katz指標(biāo)和cosine距離計(jì)算網(wǎng)絡(luò)中的路徑相似性和研究者科研興趣相似性;在此基礎(chǔ)上,構(gòu)建加權(quán)預(yù)測(cè)算法,并采用AUC指標(biāo)和F1度量確定節(jié)點(diǎn)相似性在算法中所占的比重。[結(jié)果/結(jié)論]通過實(shí)證研究發(fā)現(xiàn),在路徑相似性基礎(chǔ)上,引入一定權(quán)重的節(jié)點(diǎn)相似性,可以達(dá)到較好的預(yù)測(cè)效果。[局限]在節(jié)點(diǎn)相似性計(jì)算時(shí),僅考慮了研究者科研興趣因素,暫未考慮研究者地理位置對(duì)合作關(guān)系的影響。
[Abstract]:[aim] from the point of view of "small-world phenomenon" and "scale-free characteristic" of scientific research cooperation network, the possibility of connection of unknown links in the network is predicted. [methods] Katz index and cosine distance were used to calculate the similarity of paths and researchers' interest in scientific research. On the basis of this, the weighted prediction algorithm is constructed, and the proportion of node similarity in the algorithm is determined by using AUC index and F1 metric. [results / conclusion] through the empirical study, it is found that on the basis of path similarity, a certain weight of node similarity can be introduced to achieve a better prediction effect. [limitation] when computing the node similarity, only the researcher's interest in scientific research is considered, and the influence of the researcher's geographical position on the cooperative relationship is not taken into account for the time being.
【作者單位】： 江蘇大學(xué)科技信息研究所;
【分類號(hào)】：G353.1;O157.5
，

本文編號(hào)：2469774