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A top-k spatial-keyword query returns the k best spatio-textual objects ranked based on their proximity to the query location and relevance to the query keywords. Various index schemes have been proposed for top-k spatial-keyword queries; however, a unified framework covering all these schemes has not been proposed. In this paper, we present a generic model of index schemes for top-k spatial-keyword queries, which we call G-Index Model. First, G-Index Model is a unified framework that exhaustively investigates all the possible index schemes for top-k spatial-keyword queries. For this, we conjecture that data clustering is the key element in composing various index schemes and generate index schemes as combinations of clustering. The result shows that all the existing methods map to those generated by G-Index Model. Using G-Index Model, we also discover two new methods that have not been …