Vol.58, No.3, 2019, pp.845-857, doi:10.32604/cmc.2019.03678
OPEN ACCESS
ARTICLE
Dynamic Trust Model Based on Service Recommendation in Big Data
  • Gang Wang1,*, Mengjuan Liu2
Xi’an University of Finance and Economics, Xi’an, 710100, China.
Shaanxi Radio and Television University, Xi’an, 710068, China.
* Corresponding Author: Gang Wang. Email: .
Abstract
In big data of business service or transaction, it is impossible to provide entire information to both of services from cyber system, so some service providers made use of maliciously services to get more interests. Trust management is an effective solution to deal with these malicious actions. This paper gave a trust computing model based on service-recommendation in big data. This model takes into account difference of recommendation trust between familiar node and stranger node. Thus, to ensure accuracy of recommending trust computing, paper proposed a fine-granularity similarity computing method based on the similarity of service concept domain ontology. This model is more accurate in computing trust value of cyber service nodes and prevents better cheating and attacking of malicious service nodes. Experiment results illustrated our model is effective.
Keywords
Trust model, recommendation trust, content similarity, ontology, big data.
Cite This Article
G. . Wang and M. . Liu, "Dynamic trust model based on service recommendation in big data," Computers, Materials & Continua, vol. 58, no.3, pp. 845–857, 2019.
This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.