Abstract
In this work, we investigate the problem of diversifying top-k geosocial queries. To do so, we model the diversification objective as a bi-criteria objective that maximizes both user diversity and geosocial proximity. Due to the intractability of the problem, discovering the ideal results is only possible for limited datasets. Consequently, we introduce two heuristic algorithms to address this challenge. Our experimental findings, based on real-world geosocial datasets, demonstrate that the proposed algorithms surpass existing methods in terms of runtime performance and accuracy.
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Abedi Firouzjaei, H., Gupta, D., Nørvåg, K. (2023). Diversification of Top-k Geosocial Queries. In: Abelló, A., et al. New Trends in Database and Information Systems. ADBIS 2023. Communications in Computer and Information Science, vol 1850. Springer, Cham. https://doi.org/10.1007/978-3-031-42941-5_6
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DOI: https://doi.org/10.1007/978-3-031-42941-5_6
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