Automatic Cross-City API Matching for Urban Service Collaboration Based on Semantics

Abstract

In China, many government platforms begin to offer interfaces to each other for establishing urban service collaboration systems. However, it is expensive and tedious to migrate a successful collaboration procedure from one city to another as there are no uniform standards on API definitions. In this paper, we aim to develop a method that can match the cross-city APIs for service collaboration migration. We consider the matching task as a binary classification problem. A semantic feature engineering scheme is proposed and the matching is achieved via an XGBoost classifier. Experiments demonstrate the effectiveness of the proposed method.