Obnoxious facility location on graphs
SIAM Journal on Discrete Mathematics
A comparison of p-dispersion heuristics
Computers and Operations Research
Improving recommendation lists through topic diversification
WWW '05 Proceedings of the 14th international conference on World Wide Web
Cover trees for nearest neighbor
ICML '06 Proceedings of the 23rd international conference on Machine learning
Proceedings of the Second ACM International Conference on Web Search and Data Mining
It takes variety to make a world: diversification in recommender systems
Proceedings of the 12th International Conference on Extending Database Technology: Advances in Database Technology
An axiomatic approach for result diversification
Proceedings of the 18th international conference on World wide web
Efficient Computation of Diverse Query Results
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Preference-aware publish/subscribe delivery with diversity
Proceedings of the Third ACM International Conference on Distributed Event-Based Systems
Using trees to depict a forest
Proceedings of the VLDB Endowment
Structured search result differentiation
Proceedings of the VLDB Endowment
ACM SIGMOD Record
On query result diversification
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Incremental diversification for very large sets: a streaming-based approach
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
Diversification and refinement in collaborative filtering recommender
Proceedings of the 20th ACM international conference on Information and knowledge management
DisC diversity: result diversification based on dissimilarity and coverage
Proceedings of the VLDB Endowment
SkyDiver: a framework for skyline diversification
Proceedings of the 16th International Conference on Extending Database Technology
Top-k diversity queries over bounded regions
ACM Transactions on Database Systems (TODS)
POIKILO: a tool for evaluating the results of diversification models and algorithms
Proceedings of the VLDB Endowment
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Result diversification has recently attracted considerable attention as a means of increasing user satisfaction in recommender systems, as well as in web and database search. In this paper, we focus on the problem of selecting the k-most diverse items from a result set. Whereas previous research has mainly considered the static version of the problem, in this paper, we exploit the dynamic case in which the result set changes over time, as for example, in the case of notification services. We define the Continuous k-Diversity Problem along with appropriate constraints that enforce continuity requirements on the diversified results. Our proposed approach is based on cover trees and supports dynamic item insertion and deletion. The diversification problem is in general NP-complete; we provide theoretical bounds that characterize the quality of our solution based on cover trees with respect to the optimal solution. Finally, we report experimental results concerning the efficiency and effectiveness of our approach on a variety of real and synthetic datasets.