How to Reduce Confirmation Bias using Linked Open Data Knowledge Repository
Hyun Jung Lee, Bong‐Won Park · 2020
In this research, we are focusing on the reduction of confirmation bias of provision of information and knowledge. Nowadays, it is very common to provide customized information that users need. This kind of a service is applied to everywhere such as e-commerce sites, YouTube social networks, search engines, news sites, online-contents services delivery sites and so on. However, this unfortunately puts the risk of being open only to narrow information. Thus, they may be separated from the general information. In an environment where custom information is common, we are exposed to vulnerability to acquire the balanced knowledge. Therefore, this study proposes a method to reduce possible confirmation bias using knowledge graph with semantic structured data. For the calculation of similarity of associative and contrast between comparatives, we adopt the MSSD and MDSD using Boolean logical processing.