Buqing Cao

We propose an integrated content and network-based service clustering and Web APIs recommendation method for Mashup development. Expand

We present Active Web Service Recommendation, an effective Web service recommendation system based on users' usage history to actively recommend Web services to users. Expand

We present an approach to recommend Mashup services to users based on user interest and social network of services. Expand

This paper propose a new Service-Oriented QOS-Assured cloud computing architecture which include physical device and virtual resource layer, cloud service provision layer, Cloud service management and multi-agent layer to support QOS -Assured Cloud service provision and request. Expand

We propose, in this paper, an augmented LDA model (named WE-LDA) which leverages the high-quality word vectors to improve the performance of Web services clustering. Expand

The last decade has witnessed a tremendous growth of web services as a major technology for sharing data, computing resources, and programs on the web. Expand

This paper proposes a Mashup service recommendation approach based on Content Similarity and Collaborative Filtering, named as CSCF, and the experiments are performed to validate the feasibility and effectiveness. Expand

This paper proposes a novel domain-aware Mashup service clustering method with high accuracy and good efficiency by exploiting LDA topic model built from multiple data sources, to improve the quality of Mashup-based software development. Expand

We propose a Mashup service clustering method based on an integration of service content and network via exploiting a two-level topic model to mine latent topics for representing functional features of Mashup services. Expand