Improving Human-Computer Interaction by Developing Culture-sensitive Applications based on Common Sense Knowledge

TL;DR

This paper explores how integrating culture-sensitive common sense knowledge into human-computer interaction can enhance system intuitiveness and personalization across diverse user groups.

Contribution

It introduces LIA's architecture and methods for acquiring, representing, and utilizing common sense knowledge to improve HCI with cultural sensitivity.

Findings

Common sense knowledge improves interface intuitiveness

Cultural differences enable personalized feedback

Proposed architecture supports natural language processing

Abstract

The advent of Web 3.0, claiming for personalization in interactive systems (Lassila & Hendler, 2007), and the need for systems capable of interacting in a more natural way in the future society flooded with computer systems and devices (Harper et al., 2008) show that great advances in HCI should be done. This chapter presents some contributions of LIA for the future of HCI, defending that using common sense knowledge is a possibility for improving HCI, especially because people assign meaning to their messages based on their common sense and, therefore, the use of this knowledge in developing user interfaces can make them more intuitive to the end-user. Moreover, as common sense knowledge varies from group to group of people, it can be used for developing applications capable of giving different feedback for different target groups, as the applications presented along this chapter illustrate, allowing, in this way, interface personalization taking into account cultural issues. For the purpose of using common sense knowledge in the development and design of computer systems, it is necessary to provide an architecture that allows it. This chapter presents LIAs approaches for common sense knowledge acquisition, representation and use, as well as for natural language processing, contributing with those ones who intent to get into this challenging world to get started.