In　the　procedure　of　exploring　science-technology　linkages,　non-patent　literature　(NPL)　in　patents,　particularly　scientific　NPL,　is　considered　to　signal　the　relatedness　between　the　developed　technology　and　the　cited　science.　However,　many　prior　art　search　tools　may　not　be　powered　with　the　cross-collection　recommendation　technique,　or　have　limited　cross-collection　recommendation　capabilities.　In　this　paper,　we　present　an　approach　to　recommend　scientific　NPL　for　a　focal　patent　on　the　basis　of　heterogeneous　information　network.　This　study　views　this　cross-collection　recommendation　problem　as　a　link　prediction　problem　on　the　basis　of　meta-path　counting　approach.　Extensive　experiments　on　DrugBank　dataset　in　the　pharmaceutical　field　indicate　that　our　approach　is　feasible　and　effective.　This　work　provides　a　novel　perspective　on　scientific　NPL　recommendation　for　a　focal　patent　and　opens　up　further　possibilities　for　the　linkages　between　science　and　technology.　Nevertheless,　more　experiments　in　other　fields　are　required　to　verify　the　recommended　effects　of　the　approach　proposed　in　this　study.