Research Article
A Deep Recommendation Framework for Completely New Users in Mashup Creation
@INPROCEEDINGS{10.1007/978-3-030-67537-0_33, author={Yanmei Zhang and Jinglin Su and Shiping Chen}, title={A Deep Recommendation Framework for Completely New Users in Mashup Creation}, proceedings={Collaborative Computing: Networking, Applications and Worksharing. 16th EAI International Conference, CollaborateCom 2020, Shanghai, China, October 16--18, 2020, Proceedings, Part I}, proceedings_a={COLLABORATECOM}, year={2021}, month={1}, keywords={Service recommendation Recommendation framework Completely new user Deep neural network Mashup}, doi={10.1007/978-3-030-67537-0_33} }- Yanmei Zhang
Jinglin Su
Shiping Chen
Year: 2021
A Deep Recommendation Framework for Completely New Users in Mashup Creation
COLLABORATECOM
Springer
DOI: 10.1007/978-3-030-67537-0_33
Abstract
When service business is in evolution from B2B to B2C model, a cold-start problem raises for service composition due to the completely new clients with no historical records. Therefore, it is of great importance to solve the cold-start problem brought by completely new users. In this paper, we propose a recommendation framework for completely new users in Mashup creation based on deep-learning technology. Firstly, this framework extracts the mapping relationship between Mashup description and APIs offline by the deep neural network. Then, when the completely new users have the Mashup demands online, the matching APIs are recommended for them by using the mapping relationship. The experimental results with real-world datasets show that our proposed model outperforms the state-of-the-art ones in term of both accuracy and recall rate. The accuracy of the proposed method is 1.34 times higher than that of the state-of-the-art methods, and the recall rate is 1.55 times higher than that of the state-of-the-art methods. Moreover, considering that the new user history invocational data is very sparse, the performance of the proposed method can be greatly improved on the denser dataset.
