As　more　and　more　multi-view　data　are　collected,　how　to　apply　the　traditional　clustering　algorithm　to　multi-view　data　has　been　studied　widely.　Among　them,　the　K-means　clustering　algorithm　is　extended　because　of　its　efficiency　on　large-scale　datasets.　Based　on　the　K-means　clustering　algorithm　and　the　multi-view　data　without　domain　knowledge,　this　paper　presents　a　clustering　algorithm　based　on　internal　constrained　multi-view　K-means　(ICMK).　This　paper　also　evaluates　the　proposed　method　on　three　standard　datasets　(digits　dataset,　IS　dataset,　WTP　dataset),　and　compares　with　some　baseline　methods.　The　experiment　results　show　that　ICMK　can　produce　a　good　view　interaction　structure　automatically　and　higher　quality　clustering　results.