Towards supporting complex retrieval tasks through graph-based information retrieval and visual analytics

The retrieval result analysis approaches of existing retrieval solutions tend to be either too simple, provide too few features for exploring retrieval results or are very narrowly focused. We present an enhanced approach that attempts to address these issues and help the wider community to get more insight from their retrieved data. To this end, this paper presents an enhanced graph-based retrieval prototype built on the Collaboration Spotting platform. It combines information retrieval and visual analytics concepts to provide an advanced solution for data retrieval and exploration. It enables users to retrieve information, explore it from different perspectives using a graph representation and perform further searches based on their navigation and selection interactively. Compared to traditional retrieval solutions, a search action in CS can reveal more detailed aspects/techniques when visually analysing the search output. To gain initial feedback, we interviewed five domain experts in related fields. Findings reveal that the developed retrieval approach provides users with helpful ways of exploring search results and provides mechanisms of connecting features that are not explicitly linked otherwise. Furthermore, several research directions and improvements have been identified for future work, which should be addressed.