A Cloud API Personalized Recommendation Method Based on Multiple Attribute Features and Mashup Requirement Attention

In current mashup-oriented cloud API recommendation systems, insufficient attention to personalized development requirements remains a common issue, particularly regarding developers' needs for attributes such as functionality similarity and complementarity. This paper proposes a novel approach...

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Bibliographic Details
Published in:	IEEE access Vol. 13; pp. 13285 - 13299
Main Authors:	Shen, Limin, Wang, Yuying, Li, Chengyu, Chen, Zhen
Format:	Journal Article
Language:	English
Published:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Accuracy Attention mechanism Blogs cloud application programming interface Collaboration Customization Data mining Ecosystems Feature extraction Graph neural networks Graphical representations mashup-oriented Mashups multiple attribute features personalized recommendation Recommender systems Semantics Social networking (online) Tagging
ISSN:	2169-3536, 2169-3536
Online Access:	Get full text
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