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Deep learning framework for multi-round service bundle recommendation in iterative mashup development

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成果类型:
期刊论文
作者:
Ma, Yutao;Geng, Xiao;Wang, Jian;He, Keqing;Athanasopoulos, Dionysis
通讯作者:
Jian Wang
作者机构:
[Wang, Jian; Geng, Xiao; He, Keqing; Ma, Yutao] Wuhan Univ, Sch Comp Sci, Wuhan, Peoples R China.
[Ma, Yutao] Cent China Normal Univ, Sch Comp Sci, Wuhan, Peoples R China.
[Athanasopoulos, Dionysis] Queens Univ Belfast, Sch Elect Elect Engn & Comp Sci, Belfast, Antrim, North Ireland.
通讯机构:
[Jian Wang] S
School of Computer Science, Wuhan University, Wuhan, China
语种:
英文
关键词:
attention;deep learning;mashup development;recommender systems;service bundle
期刊:
智能技术学报
ISSN:
2468-2322
年:
2022
卷:
8
期:
3
页码:
914-930
基金类别:
This work was supported by the National Key Research and Development Program of China (No. 2020AAA0107705) and the National Science Foundation of China (Nos. 61972292 and 62032016).
机构署名:
本校为其他机构
院系归属:
计算机学院
摘要:
Recent years have witnessed the rapid development of service-oriented computing technologies. The boom of Web services increases software developers' selection burden in developing new service-based systems such as mashups. Timely recommending appropriate component services for developers to build new mashups has become a fundamental problem in service-oriented software engineering. Existing service recommendation approaches are mainly designed for mashup development in the single-round scenario. It is hard for them to effectively update recommendation results according to developers' requirem...

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