Learning Agent for a Service-Oriented Context-Aware Recommender System in Heterogeneous Environment

Authors

  • Piotr Nawrocki AGH University of Science and Technology, Kraków
  • Bartłomiej Śnieżyński AGH University of Science and Technology, Kraków
  • Jakub Czyżewski AGH University of Science and Technology, Kraków

Keywords:

Service-oriented recommender system, context-aware, heterogeneous environment, learning agent, supervised learning, cloud computing

Abstract

Traditional recommender systems provide users with customized recommendations of products or services. They employ various technologies and algorithms in order to search and select the best options available while taking into account the user's context. Increasingly often, such systems run on devices in heterogeneous environments (including mobile devices) making use of their functionalities: various sensors (e.g. movement, light), wireless data transmission technologies and positioning systems (e.g. GPS) among others. In this paper, we propose an innovative recommender system that determines the best service (including photo and movie conversion) and simultaneously accommodates the context of the device in a heterogeneous environment. The system allows the choice between various service providers that make their resources available using cloud computing as well as having the services performed locally. In order to determine the best possible recommendation for users, we employ the concept of learning agents, which has not been thoroughly researched in connection with recommender systems so far.

Downloads

Download data is not yet available.

Downloads

Published

2017-02-07

How to Cite

Nawrocki, P., Śnieżyński, B., & Czyżewski, J. (2017). Learning Agent for a Service-Oriented Context-Aware Recommender System in Heterogeneous Environment. COMPUTING AND INFORMATICS, 35(5), 1005–1026. Retrieved from http://www.cai.sk/ojs/index.php/cai/article/view/3354