Community　detection　based　on　edge　clustering　is　capable　of　detecting　overlapping　communities　naturally.　However,　it　engenders　the　problems　of　obscure　belongingness　of　the　nodes　on　community　borders　and　the　excessive　overlap　of　communities.　In　this　paper,　an　overlapping　community　detection　based　on　edge　density　clustering(OCDEDC)　algorithm　is　proposed.　Firstly,　density　clustering　based　on　edges　is　employed　to　extract　core　edge　communities.　Next,　a　partitioning　strategy　is　designed　to　dispatch　border　edges　to　its　closest　core　edge　community.　In　addition,　a　strategy　based　on　the　degrees　and　community　belongingness　of　edges　is　designed　to　handle　the　isolated　edges,　and　thus　the　excessive　overlap　of　communities　is　avoided.　Finally,　edge　communities　are　transformed　back　into　node　communities　©　2018,　Science　Press.　All　right　reserved.