A graph-based trust-enhanced recommender system for service selection in IOT
| Title | A graph-based trust-enhanced recommender system for service selection in IOT |
| Publication Type | Conference Paper |
| Year of Publication | 2017 |
| Authors | Nizamkari, N. S. |
| Conference Name | 2017 International Conference on Inventive Systems and Control (ICISC) |
| ISBN Number | 978-1-5090-4715-4 |
| Keywords | Collaboration, collaborative filtering, collaborative filtering recommendation algorithm, computer theory, control systems, graph theory, graph-based trust-enhanced recommender system, Human Behavior, human factors, Internet of Things, IoT, pubcrawl, recommender systems, reliable service, security of data, service selection problem, social Internet of Things, Social network services, Temperature measurement, Trust, Trusted Computing |
| Abstract | In an Internet of Things (IOT) network, each node (device) provides and requires services and with the growth in IOT, the number of nodes providing the same service have also increased, thus creating a problem of selecting one reliable service from among many providers. In this paper, we propose a scalable graph-based collaborative filtering recommendation algorithm, improved using trust to solve service selection problem, which can scale to match the growth in IOT unlike a central recommender which fails. Using this recommender, a node can predict its ratings for the nodes that are providing the required service and then select the best rated service provider. |
| URL | https://ieeexplore.ieee.org/document/8068714/ |
| DOI | 10.1109/ICISC.2017.8068714 |
| Citation Key | nizamkari_graph-based_2017 |
- IoT
- Trusted Computing
- trust
- Temperature measurement
- Social network services
- Social Internet of Things
- service selection problem
- security of data
- reliable service
- recommender systems
- pubcrawl
- collaboration
- Internet of Things
- Human Factors
- Human behavior
- graph-based trust-enhanced recommender system
- graph theory
- control systems
- computer theory
- collaborative filtering recommendation algorithm
- collaborative filtering