E-Stores loose sells due to the negative biases of consumers. While salespeople give proper reasons to change consumers misbelieves, it is problematic to address those issues in an online shop. In this talk, I will present how to combine semantic graphs with logic programming and symbolic machine learning to restore consumer’s confidence. The digital agent detects what are the problems users might have and offers them explanations and valid arguments for not worry about, or why a given recommendation is more suitable than others.
The fragmentation of platforms, protocols, and standards in the Internet of Things (IoT) domains of smart home, buildings and grids poses many challenges to the realization of an ‘interconnected world’. Making devices from different producers interoperable interests both industrial entities and end-users. On the one hand, industrial manufacturers have started to understand the importance of connecting physical devices within and across domains using open standards (such as SAREF) in order to avoid vendor lock-in.
The past decade has seen significant investments in data warehouses, data lakes and data lake houses for a sizable number of organizations with the goal to integrate and access data at scale. Despite these new technical capabilities and strong leadership support, many organizations continue to face challenges when it comes to successfully understanding or retrieving meaningful insights from their data or achieving economies of scale and
alignment across the multiple data initiatives, many of these new projects are failing to demonstrate sufficient business value.