Open APIs recommendation with an ensemble-based multi-feature model

Author:

Chen Junwu,Wang YeORCID,Huang QiaoORCID,Jiang Bo,Liu Pengxiang

Funder

Zhejiang Province Natural Science Foundation

Publisher

Elsevier BV

Subject

Artificial Intelligence,Computer Science Applications,General Engineering

Reference43 articles.

1. Aznag, M., Quafafou, M., & Jarir, Z. (2014). Leveraging formal concept analysis with topic correlation for service clustering and discovery. In Proceedings of the 2014 IEEE international conference on web services.

2. A review of machine learning algorithms for identification and classification of non-functional requirements;Binkhonain;Expert Systems with Applications: X,2019

3. Mashup service clustering based on an integration of service content and network via exploiting a two-level topic model;Cao,2016

4. Integrated content and network-based service clustering and web apis recommendation for mashup development;Cao;IEEE Transactions on Services Computing,2020

5. Qos-aware service recommendation based on relational topic model and factorization machines for iot mashup applications;Cao;Journal of Parallel and Distributed Computing,2019

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