The Human Phenotype Ontology (HPO) was developed to be a semantically computable vocabulary that captures the phenotypic abnormalities found in human diseases discovered through biomedical research. Usage of this ontology facilitates the translation between genotype and phenotype. Many studies have been conducted to accelerate the implementation of precision medicine into clinical practice by utilizing the informative contents provided in the HPO. No work, however, has been done in constructing a distributed representation for nodes in HPO to provide a deep insight of phenotypic similarities by analyzing its graph structure. Node2vec is a model for generating node embeddings based on large networks. In this study, we constructed node embeddings for the HPO leveraging node2vec to assist phenotypic similarity measurement. A downstream application on link prediction driven by HPO embedding achieved 0.81 ROAUC and 0.75 F-measure. A use case study was conducted on idiopathic pulmonary fibrosis (IPF) and we demonstrated the potential possibility of using HPO embeddings in assisting phenotypic similarity measurement.