基于余弦相似自適應(yīng)加權(quán)視圖重構(gòu)的不完全多視圖聚類算法

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中圖分類號(hào)：TP18文獻(xiàn)標(biāo)志碼：A

Incomplete Multi-view Clustering Algorthm Based on Adaptive Weighing View Reconstruction with Cosine Similarity

CHEN Yongtaia，QIU Ye?，WAN Minghua?，YANG Guowei? （a.ScholofEngineringAudit，b.SchoolofComputerScience，NanjingAuditUniversity，Nanjing815，Jiangsu，Cina

Abstract：To solvetheproblems thatmulti-view dataoften contained mising or abnormal information inpractical applicationsandtheexisting incompletemulti-viewclustering methodsfailedtoadequatelyrepresenttheoriginaldatasimilarity intheprocessofdatasimilaritymatrixoptimization，increasedthecomputationalcomplexityandignoredthediferenceof discriminant infor-mation between views，an incomplete multi-view clustering algorithmbasedonadaptive weighting view reconstruction with cosine similarity was proposed.Natural alignmentof mising views was achieved by introducing alocal preservation reconstructionterm，which avoided negativeeffectsthat might be caused by filing missing views with mean values.Inthe initializationphase，the preservation of manifold structure of original multi-view data was enhanced by computing cosine similarityinthe original multi-viewspace，andanadaptive weighting strategy was employed to capture the importance of diferent views during thecomplete viewconstruction process.The clustering experiments were caried outin4benchmark datasetsand compared with theoptimal resultsof9existing repre-sentative algorithms.Theresults showthat theaverage clusteringaccuracy，normalizedmutual informationandpurityof theproposedalgorithmare improved by 5.52% ， 8.78% and 4.77% respectively，which fully reflects the excellent incomplete multi-view clustering performance of the proposed algorithm.

Keywords：incomplete multi-viewclustering；adaptive weighting；cosine similarity；manifold structure；viewreconstruction

在現(xiàn)實(shí)世界中，我們經(jīng)常面對(duì)的是多個(gè)來(lái)源或由多個(gè)特征描述的數(shù)據(jù)，這種數(shù)據(jù)被稱為多視圖數(shù)據(jù)[1]。（剩余13939字）