A Novel Approach for Web Service Recommendation Based on Advanced Trust Relationships

Duan, Lijun; Tian, Hao; Liu, Kun

doi:10.3390/info10070233

Cited by 7 publications

(1 citation statement)

References 12 publications

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“…With the rapid increase in the number of Web services, how to obtain appropriate Web services has become a difficult problem for developers. A service recommendation method can personalize Web service recommendations [1][2][3][4][5][6][7][8] for developers. However, the actively recommended Web services are often popular services that developers have used before.…”

Section: Introductionmentioning

confidence: 99%

Service Discovery Method Based on Knowledge Graph and Word2vec

Zhou

Yang

et al. 2022

Electronics

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Mashup is a new type of application that integrates multiple Web APIs. For mashup application development, the quality of the selected APIs is particularly important. However, with the rapid development of Internet technology, the number of Web APIs is increasing rapidly. It is unrealistic for mashup developers to manually select appropriate APIs from a large number of services. For existing methods, there is a problem of data sparsity, because one mashup is related to a few APIs, and another problem of over-reliance on semantic information. To solve these problems in current service discovery approaches, we propose a service discovery approach based on a knowledge map (SDKG). We embed service-related information into the knowledge graph, alleviating the impact of data sparsity and mining deep relationships between services, which improves the accuracy of service discovery. Experimental results show that our approach has obvious advantages in accuracy compared with the existing mainstream service discovery approaches.

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Section: Introductionmentioning

confidence: 99%

Service Discovery Method Based on Knowledge Graph and Word2vec

Zhou

Yang

et al. 2022

Electronics

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Service Availability Assessment Model Based on User Tolerance

Zhang

Chu

et al. 2023

Mobile Netw Appl

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A Social-Relationships-Based Service Recommendation System for SIoT Devices

Khelloufi

Ning

Dhelim

et al. 2021

IEEE Internet Things J.

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The Social Internet of Things (SIoT), is revolutionizing how we interact with our everyday lives. By adding the social dimension to connecting devices, the SIoT has the potential to drastically change the way we interact with smart devices. This connected infrastructure allows for unprecedented levels of convenience, automation, and access to information, allowing us to do more with less effort. However, this revolutionary new technology also brings an eager need for service recommendation systems. As the SIoT grows in scope and complexity, it becomes increasingly important for businesses and individuals, and SIoT objects alike to have reliable sources for products, services, and information that are tailored to their specific needs. Few works have been proposed to provide service recommendations for SIoT environments. However, these efforts have been confined to only focusing on modeling user-item interactions using contextual information, devices' SIoT relationships, and correlation social groups but these schemes do not account for latent semantic item-item structures underlying the sparse multi-modal contents in SIoT environment. In this paper, we propose a latent-based SIoT recommendation system that learns item-item structures and aggregates multiple modalities to obtain latent item graphs which are then used in graph convolutions to inject high-order affinities into item representations. Experiments showed that the proposed recommendation system outperformed state-of-theart SIoT recommendation methods and validated its efficacy at mining latent relationships from multi-modal features.

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A Novel Approach for Web Service Recommendation Based on Advanced Trust Relationships

Cited by 7 publications

References 12 publications

Service Discovery Method Based on Knowledge Graph and Word2vec

Service Discovery Method Based on Knowledge Graph and Word2vec

Service Availability Assessment Model Based on User Tolerance

A Social-Relationships-Based Service Recommendation System for SIoT Devices

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