User　interests　are　usually　distributed　in　different　systems　on　the　Web.　Traditional　user　interest　modeling　methods　are　not　designed　for　integrating　and　analyzing　interests　from　multiple　sources,　hence,　they　are　not　very　effective　for　obtaining　comparatively　complete　description　of　user　interests　in　the　distributed　environment.　In　addition,　previous　studies　concentrate　on　the　text　level　analysis　of　user　interests,　while　semantic　relationships　among　interests　are　not　fully　investigated.　This　might　cause　incomplete　and　incorrect　understanding　of　the　discovered　interests,　especially　when　interests　are　from　multiple　sources.　In　this　paper,　we　propose　an　approach　of　user　interest　modeling　based　on　multi-source　personal　information　fusion　and　semantic　reasoning.　We　give　different　fusion　strategies　for　interest　data　from　multiple　sources.　Further　more,　we　investigate　the　semantic　relationship　between　users＇　explicit　interests　and　implicit　interests　by　reasoning　through　concept　granularity.　Semantic　relatedness　among　interests　are　also　briefly　illustrated　for　information　fusion.　Illustrative　examples　based　on　multiple　sources　on　the　Web　(e.g.　microblog　system　Twitter,　social　network　sites　Facebook　and　LinkedIn,　personal　homepage,　etc.)　show　that　proposed　approach　is　potentially　effective.　©　2011　Springer-Verlag.