电子与信息学报
電子與信息學報
전자여신식학보
JOURNAL OF ELECTRONICS & INFORMATION TECHNOLOGY
2014年
2期
325-331
,共7页
复杂网络%链路预测%预测误差修正
複雜網絡%鏈路預測%預測誤差脩正
복잡망락%련로예측%예측오차수정
Complex network%Link prediction%Prediction error correction
论文主要针对时序链路预测方法进行研究。分析了静态链路预测方法的弊端,认为忽视网络演化趋势信息会对链路预测产生负面影响;还提出了链路预测误差的概念用于描述网络趋势信息,并以此为基础提出一种基于预测误差修正的时序链路预测方法。该方法首先对待预测时刻之前一个时间窗口内的多幅网络图分别采用静态链路预测方法进行预测,记录每次的预测误差并计算其修正值,最后对待测时刻静态预测结果进行修正得到最终预测结果。通过在两个真实网络数据集上进行系列实验表明,该方法较大提升了静态链路预测方法的预测精确度,与另一种典型的时序链路预测方法相比其精度也有所提升,且算法时间复杂度较低。另外,实验中还发现链路预测误差序列与网络链路总数序列存在“镜面对称”关系,分析其内在原因证明了所提方法的普适性。
論文主要針對時序鏈路預測方法進行研究。分析瞭靜態鏈路預測方法的弊耑,認為忽視網絡縯化趨勢信息會對鏈路預測產生負麵影響;還提齣瞭鏈路預測誤差的概唸用于描述網絡趨勢信息,併以此為基礎提齣一種基于預測誤差脩正的時序鏈路預測方法。該方法首先對待預測時刻之前一箇時間窗口內的多幅網絡圖分彆採用靜態鏈路預測方法進行預測,記錄每次的預測誤差併計算其脩正值,最後對待測時刻靜態預測結果進行脩正得到最終預測結果。通過在兩箇真實網絡數據集上進行繫列實驗錶明,該方法較大提升瞭靜態鏈路預測方法的預測精確度,與另一種典型的時序鏈路預測方法相比其精度也有所提升,且算法時間複雜度較低。另外,實驗中還髮現鏈路預測誤差序列與網絡鏈路總數序列存在“鏡麵對稱”關繫,分析其內在原因證明瞭所提方法的普適性。
논문주요침대시서련로예측방법진행연구。분석료정태련로예측방법적폐단,인위홀시망락연화추세신식회대련로예측산생부면영향;환제출료련로예측오차적개념용우묘술망락추세신식,병이차위기출제출일충기우예측오차수정적시서련로예측방법。해방법수선대대예측시각지전일개시간창구내적다폭망락도분별채용정태련로예측방법진행예측,기록매차적예측오차병계산기수정치,최후대대측시각정태예측결과진행수정득도최종예측결과。통과재량개진실망락수거집상진행계렬실험표명,해방법교대제승료정태련로예측방법적예측정학도,여령일충전형적시서련로예측방법상비기정도야유소제승,차산법시간복잡도교저。령외,실험중환발현련로예측오차서렬여망락련로총수서렬존재“경면대칭”관계,분석기내재원인증명료소제방법적보괄성。
The temproral link prediction method is investigated in this paper. The disadvantages of the static link prediction methods are analyzed, considering that ignoring the evolving information of networks will lead to a negative impact on link predicting. The concept of link prediction error is proposed to describe the evolving information of networks, and a temporal link prediction method is proposed based on the prediction error correction. Firstly, several static link prediction are carried out using each graph in the previous periods window, and then the prediction errors are recorded and used for calculating the modification value. At last, the final prediction result is acquired through refining the static prediction result with the modification value. Several experiments are conducted using two real network datasets. The results show that the proposed method achieves better performance than the static link prediction methods and a typical temporal link prediction method. In addition, it can be found that a relation of‘mirror symmetry’ exists between prediction error series and total link number series, which demonstrates the universality of the proposed method.