Customizing information delivery to project stakeholders in the smart city

In the smart city, citizens are integral participants in the decision making process. They possess equally important knowledge to that of professionals. Effectively informing them about new project features is the first step in engaging them in the decision making and harnessing their knowledge. However, given the complexity and diversity of project information, citizens could face an information overload. Our objective is to support the delivery of the right information to the right person; and doing so in an adaptive manner that recognizes the needs of local context. We have developed a system that allows users to profile their information needs based on an ontology of user communications. Recommender algorithms are then used to match user profile to the most relevant knowledge items, such as documents, web pages, and tagged videos or images. Users who wish to rate or tag documents can do so through using concepts from the ontology or free text. If free text is used, semantic analysis is conducted to extract relevant tags. Tags are then fed-back into the recommender system to enhance its accuracy. Capturing community tags provides a good opportunity to use crowd input to contextualise the matching algorithms.