A Novel Blockchain-Based Responsible Recommendation System for Service Process Creation and Recommendation

IF 7.2 4区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Tieliang Gao, Li Duan, Lufeng Feng, Wei Ni, Quan Z. Sheng
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引用次数: 0

Abstract

Service composition platforms play a crucial role in creating personalized service processes. Challenges, including the risk of tampering with service data during service invocation and the potential single point of failure in centralized service registration centers, hinder the efficient and responsible creation of service processes. This paper presents a novel framework called Context-Aware Responsible Service Process Creation and Recommendation (SPCR-CA), which incorporates blockchain, Recurrent Neural Networks (RNNs), and a Skip-Gram model holistically to enhance the security, efficiency, and quality of service process creation and recommendation. Specifically, the blockchain establishes a trusted service provision environment, ensuring transparent and secure transactions between services and mitigating the risk of tampering. The RNN trains responsible service processes, contextualizing service components and producing coherent recommendations of linkage components. The Skip-Gram model trains responsible user-service process records, generating semantic vectors that facilitate the recommendation of similar service processes to users. Experiments using the Programmable-Web dataset demonstrate the superiority of the SPCR-CA framework to existing benchmarks in precision and recall. The proposed framework enhances the reliability, efficiency, and quality of service process creation and recommendation, enabling users to create responsible and tailored service processes. The SPCR-CA framework offers promising potential to provide users with secure and user-centric service creation and recommendation capabilities.

基于区块链的新型服务流程创建和推荐责任推荐系统
服务组合平台在创建个性化服务流程方面发挥着至关重要的作用。服务调用过程中服务数据被篡改的风险以及集中式服务注册中心潜在的单点故障等挑战阻碍了高效、负责任地创建服务流程。本文提出了一种名为 "情境感知负责任服务流程创建和推荐(SPCR-CA)"的新型框架,该框架将区块链、循环神经网络(RNN)和Skip-Gram模型结合在一起,全面提高了服务流程创建和推荐的安全性、效率和质量。具体来说,区块链建立了一个可信的服务提供环境,确保服务之间的交易透明、安全,并降低篡改风险。RNN 训练负责任的服务流程,将服务组件上下文化,并对链接组件提出一致的建议。Skip-Gram模型训练负责任的用户服务流程记录,生成语义向量,便于向用户推荐类似的服务流程。使用可编程网络数据集进行的实验表明,SPCR-CA 框架在精确度和召回率方面优于现有基准。所提出的框架提高了服务流程创建和推荐的可靠性、效率和质量,使用户能够创建负责任的、量身定制的服务流程。SPCR-CA 框架有望为用户提供安全且以用户为中心的服务创建和推荐功能。
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来源期刊
ACM Transactions on Intelligent Systems and Technology
ACM Transactions on Intelligent Systems and Technology COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, INFORMATION SYSTEMS
CiteScore
9.30
自引率
2.00%
发文量
131
期刊介绍: ACM Transactions on Intelligent Systems and Technology is a scholarly journal that publishes the highest quality papers on intelligent systems, applicable algorithms and technology with a multi-disciplinary perspective. An intelligent system is one that uses artificial intelligence (AI) techniques to offer important services (e.g., as a component of a larger system) to allow integrated systems to perceive, reason, learn, and act intelligently in the real world. ACM TIST is published quarterly (six issues a year). Each issue has 8-11 regular papers, with around 20 published journal pages or 10,000 words per paper. Additional references, proofs, graphs or detailed experiment results can be submitted as a separate appendix, while excessively lengthy papers will be rejected automatically. Authors can include online-only appendices for additional content of their published papers and are encouraged to share their code and/or data with other readers.
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