Sustainable　development　is　a　meaningful　indicator　for　high-tech　transfer.　High-tech　transfer　monitoring　is　an　effectual　measure　for　high-tech　transfer　evaluation.　This　paper　takes　high-tech　transfer　projects　as　a　data　source,　considers　the　key　words　and　new　words　extracted　by　NLPIR　from　the　projects,　and　proposes　a　high-tech　word　similarity　calculating　method　based　on　morphological　similarity,　word　length　similarity　and　individual　character　similarity.　Applied　this　method　onto　high-tech　word　similarity　measurement,　and　acquires　high-tech　word　similarity　matrixes.　Cluster　based　on　this　high-tech　word　similarity　matrix.　Construct　high-tech　ontology,　according　to　cluster　result.　Extract　the　corresponding　high-tech　monitoring　indicators　and　values　of　high-tech　ontology　through　Regex.　Finally　construct　high-tech　transfer　monitoring　ontology,　and　monitor　the　sustainable　development　of　high-tech　transfer.　Formulating　high-tech　word　similarity　computing　software　achieves　high-tech　word　similarity　computer　measurement　and　verifies　the　feasibility　and　accuracy　of　this　computing　model.　©　(2014)　Trans　Tech　Publications,　Switzerland.