Maximizing diversity over clustered data∗

Guangyi Zhang
Guangyi Zhang

Proceedings of the 2020 SIAM International Conference on Data Mining, pp. 649-657, 2020.

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Abstract:

Maximum diversity aims at selecting a diverse set of high-quality objects from a collection, which is a fundamental problem and has a wide range of applications, e.g., in Web search. Diversity under a uniform or partition matroid constraint naturally describes useful cardinality or budget requirements, and admits simple approximation algo...More

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