Traditional　database　search　uses　pattern　match　in　the　comparison　process.　For　a　query　with　some　search　words,　tuples　are　selected　only　if　the　words　of　the　tuples　exactly　match　the　query　words.　In　this　paper,　we　propose　a　new　method　for　evaluating　relational　ranking　queries　(or　top-N　queries)　with　text　attributes.　This　method　defines　semantic　distance　functions　and　utilizes　semantic　match　between　words　in　database　search.　The　attempt　is　that　tuples,　not　only　exactly　matching,　but　also　close　to　the　query　according　to　semantic　distances,　can　both　be　fetched.　The　basic　idea　of　the　method　is　to　create　an　index　based　on　WordNet　to　expand　the　tuple　words　semantically.　The　candidate　results　for　a　query　are　retrieved　by　the　index　and　a　simple　SQL　selection　statement,　and　then　top-N　answers　are　obtained.　Extensive　experiments　are　carried　out　to　measure　the　performance　of　this　new　strategy　for　the　evaluation　of　ranking　queries　over　relational　databases.