A Web Intelligent System based on Measuring the Effects of Bother

Abstract

The influence of bother measures the extent to which a user would be bothered or annoyed by any interaction with the agent, especially when the user interacts over the Internet. This paper discusses the model of bother cost and its application in web services that wish to obtain personal information from those users. Thereby, we propose a Comprehensive and Hierarchical Bother Cost Model (CHBCM) which extends traditional bother cost by including Web-specific factors for Web interactions. Simulation experiments show that the agent that uses a bother cost model has more benefit to the user and modeling bother cost is indeed worthwhile. Hence, Web intelligent agents that contain CHBCM can try to reduce unnecessary interruptions while obtaining the maximum amount of information from users.