Optimising web-based information retrieval methods for horizon scanning using relevance feedback

Horizon scanning is being increasingly regarded as an instrument to support strategic decision making. It requires the systematic examination of information to identify potential threats, emerging issues and opportunities to improve resilience and decrease risk exposure. Horizon scanning can use the Web to augment the acquisition of information, though this involves a search for novel and emerging issues without knowing them beforehand. To optimise such a search, we propose the use of relevance feedback, which involves human interaction in the retrieval process so as to improve results. As a proof-of-concept demonstration, we have carried out a horizon scanning exercise which showed that our implementation of relevance feedback was able to maintain the retrieval of relevant documents constant over the length of the experiment, without any reduction. This represents an improvement over previous studies where relevance feedback was not considered.