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Web service quality of service prediction via regional reputation-based matrix factorization

Ghafouri, S. H ; Sharif University of Technology | 2021

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  1. Type of Document: Article
  2. DOI: 10.1002/cpe.6318
  3. Publisher: John Wiley and Sons Ltd , 2021
  4. Abstract:
  5. Quality of Service (QoS) of Web services plays an essential role in selecting Web services by consumers. The dynamic QoS attributes of Web services have different values for different users. Therefore, the value of many Web services' QoS features for many users are undetermined, and these values should be predicted. The collaborative filtering (CF) method is one of the most successful approaches to predict these values. CF-based methods use the QoS values contributed by the other users for prediction and, consequently, the values contributed by unreliable users can decrease the accuracy of prediction. To utilize the reputation of users can be regarded as one of the conventional approaches to overcome this problem. In this paper, we have defined a concept called regional reputation that represents the reputation of a user for users in each geographical region. Regional reputation has been achieved with the combination of the location information of the users and their reputation. Subsequently, by combining this concept with the matrix factorization, we have proposed a prediction method called regional reputation-based matrix factorization. This approach has been able to improve the accuracy of prediction and be more persistent to the data contributed by unreliable users. © 2021 John Wiley & Sons Ltd
  6. Keywords:
  7. Collaborative filtering ; Factorization ; Forecasting ; Matrix algebra ; Quality of service ; Telecommunication services ; Websites ; Conventional approach ; Location information ; Matrix factorizations ; Prediction methods ; QoS attributes ; Web service qualities ; Web services
  8. Source: Concurrency and Computation: Practice and Experience ; Volume 33, Issue 17 , 2021 ; 15320626 (ISSN)
  9. URL: https://onlinelibrary.wiley.com/doi/10.1002/cpe.6318