Algorithm 1.

IMV-FCM algorithm.

Input	Multiview sample set X, number of views V, number of clustering C, iteration threshold ε, fuzzy index m, iteration number l, parameter γ.
Output	The final division matrix $\overline{U}$, the clustering center of each view zi,v, the view fusion weight matrix W = {wv,t}.
Step 1	Randomly generate fuzzy membership matrix uij,t(1≤t≤V) for each view and view fusion weight matrix W = {wv,t} for each view;
Step 2	According to Eq. 12, the cluster center zi,v of each view is updated.
Step 3	According to Eq. 13, the membership degree uij,t of each view is updated.
Step 4	According to Eq. 14, the view fusion weight matrix W = {wv,t} is updated.
Step 5	If ||Jl + 1−Jl|| < ε, the algorithm stops iterating; otherwise, it returns to Step 2.
Step 6	After the algorithm converges, the fuzzy membership of each view is output.
Step 7	According to the fuzzy membership degree of each view obtained in Step 6, Eq. 15 is used to obtain the final division matrix.