Faceted Search Systems (FSSs) have gained prominence as one of the dominant search approaches in vertical search systems. They provide facets to educate users about the information space and allow them to refine their search query and navigate back and forth between resources on a single results page. Despite the importance of this problem, it is rare to find studies dedicated solely to the investigation of facet ranking methods, nor to how this step, aside from other aspects of faceted search, affects the user’s search experience. The objective of this survey paper is to review the state of the art in research related to faceted search systems, with a focus on existing facet ranking approaches and the key challenges posed by this problem. In addition to that, this survey also investigates state-of-the-art FSS evaluation frameworks and the most commonly used techniques and metrics to evaluate facet ranking approaches. It also lays out criteria for dataset appropriateness and its needed structure to be used in evaluating facet ranking methods aside from other FSS aspects. This paper concludes by highlighting gaps in the current research and future research directions related to this area.

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