Semantic　similarity　between　concepts　is　a　fundamental　problem　and　plays　an　important　role　in　many,　applications　of　artificial　intelligence,　knowledge　sharing　and　Web　mining.　In　this　paper,　a　new,　measure　based　on　semantic　ontology　database　WordNet　is　proposed　which　combines　information　content-based　measure　and　the　edge-counting　techniques　to　measure　semantic　similarity.　＂PART-OF＂　and　＂IS-A＂　hierarchical　relations＇　influence　are　considered　on　the　semantic　similarity　in　this　paper.　Breadth-first　search　is　used　to　find　the　shortest　path　between　two　concepts.　The　similarity　of　hiberarchy　and　superposition　are　calculated　respectively.　WordNet3.0　is　employed;　JWNL1.4.1　is　used　to　operate　WordNet.　According　to　the　experiment　against　a　benchmark　set　by　human　similarity　judgment,　our　measure　achieves　a　better　result.