A two-Phase method of qos prediction for situated service recommendation

Jiapeng Dai, Donghui Lin, Toru Ishida

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Citations (Scopus)

Abstract

With the rapid growth of Web services, recommending suitable services to users has become a big challenge. The existing service recommendation works by Quality of Service (QoS) prediction fail to fully consider the influence of situation information, such as time, location, and user relations thoroughly. Two issues must be resolved to consider situation information: issue one, rating scarcity, is that there are less data to learn when importing more situations; issue two is that an effective approach is needed to adapt many situational factors. Our solution is a two-phase method: first, to overcome rating scarcity, data is augmented with estimations of unknown QoS values by learning from observable factors. The augmented data is then used to learn the important latent factors associated with the situational factors for QoS prediction. Experiments on data of real service invocations in different situations show improvement of our method in terms of QoS prediction accuracy over several existing methods, especially in the severe rating scarcity condition. In addition, analysis on parameter selection of proposed method can further assist in obtaining better QoS prediction in practical use.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Services Computing, SCC 2018 - Part of the 2018 IEEE World Congress on Services
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages137-144
Number of pages8
ISBN (Print)9781538672501
DOIs
Publication statusPublished - 2018 Sep 5
Externally publishedYes
Event2018 IEEE International Conference on Services Computing, SCC 2018 - San Francisco, United States
Duration: 2018 Jul 22018 Jul 7

Publication series

NameProceedings - 2018 IEEE International Conference on Services Computing, SCC 2018 - Part of the 2018 IEEE World Congress on Services

Conference

Conference2018 IEEE International Conference on Services Computing, SCC 2018
CountryUnited States
CitySan Francisco
Period18/7/218/7/7

Keywords

  • QoS
  • rating scarcity
  • service recommendation
  • situation

ASJC Scopus subject areas

  • Computer Science Applications
  • Computer Networks and Communications
  • Hardware and Architecture
  • Information Systems and Management

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  • Cite this

    Dai, J., Lin, D., & Ishida, T. (2018). A two-Phase method of qos prediction for situated service recommendation. In Proceedings - 2018 IEEE International Conference on Services Computing, SCC 2018 - Part of the 2018 IEEE World Congress on Services (pp. 137-144). [8456411] (Proceedings - 2018 IEEE International Conference on Services Computing, SCC 2018 - Part of the 2018 IEEE World Congress on Services). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/SCC.2018.00025