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...

Ausführliche Beschreibung

Gespeichert in:

Bibliographische Detailangaben
Veröffentlicht in:	IEEE access Jg. 13; S. 13285 - 13299
Hauptverfasser:	Shen, Limin, Wang, Yuying, Li, Chengyu, Chen, Zhen
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Piscataway IEEE 2025 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:	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-Zugang:	Volltext
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Schreiben Sie den ersten Kommentar!