Diversification of Top-k Geosocial Queries
Original version
10.1007/978-3-031-42941-5_6Abstract
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.