  Dimensionality reduction techniques are widely used for visualizing
high-dimensional data. However, support for interpreting patterns of dimension
reduction results in the context of the original data space is often
insufficient. Consequently, users may struggle to extract insights from the
projections. In this paper, we introduce DimBridge, a visual analytics tool
that allows users to interact with visual patterns in a projection and retrieve
corresponding data patterns. DimBridge supports several interactions, allowing
users to perform various analyses, from contrasting multiple clusters to
explaining complex latent structures. Leveraging first-order predicate logic,
DimBridge identifies subspaces in the original dimensions relevant to a queried
pattern and provides an interface for users to visualize and interact with
them. We demonstrate how DimBridge can help users overcome the challenges
associated with interpreting visual patterns in projections.
