Information　retrieval　model　has　been　applied　to　the　collaborative　filtering　algorithm　now.　The　belief　network　model　in　information　retrieval　is　used　to　describe　user-based　collaborative　filtering　and　item-based　collaborative　filtering　uniformly,　and　a　recommendation　algorithm　of　collaborative　filtering　graph　model　based　on　belief　network　is　put　forward.　Due　to　the　property　that　belief　network　is　convenient　to　combine　the　information　of　additional　sources,　the　expert　information　is　added　to　the　collaborative　filtering　model　to　provide　decision　support　for　the　users,　and　consequently　the　data　sparse　problem　of　the　recommendation　system　is　solved.　Experimental　results　show　that　the　proposed　algorithm　improves　the　recommendation　accuracy.　©　2016,　Science　Press.　All　right　reserved.