Inferring Service Recommendation from Natural Language API Descriptions

Software reuse through Application Programming Interfaces (APIs) is a common practice in software development. It remains a big challenge to bridge the semantic gap between user expectations and application functionality with the development of Web-based services. This paper proposes a service recommendation approach via extracting semantic relationship from natural language API descriptions and inferring. To validate our approach, large-scale experiments are conducted based on a real-world accessible service repository, ProgrammableWeb. The results show the effectiveness of our proposed approach.

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