The Grid File: An Adaptable, Symmetric Multikey File Structure
ACM Transactions on Database Systems (TODS)
Efficient and extensible algorithms for multi query optimization
SIGMOD '00 Proceedings of the 2000 ACM SIGMOD international conference on Management of data
Aggregate-Query Processing in Data Warehousing Environments
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
ACM SIGMOD Record
Efficient diversity-aware search
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
On query result diversification
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Optimized processing of multiple aggregate continuous queries
Proceedings of the 20th ACM international conference on Information and knowledge management
DoS: an efficient scheme for the diversification of multiple search results
Proceedings of the 25th International Conference on Scientific and Statistical Database Management
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The explosion of big data emphasizes the need for scalable data diversification, especially for applications based on web, scientific, and business databases. However, achieving effective diversification in a multi-user environment is a rather challenging task due to the inherent high processing costs of current data diversification techniques. In this paper, we address the concurrent diversification of multiple search results using various approximation techniques that provide orders of magnitude reductions in processing cost, while maintaining comparable quality of diversification as compared to sequential methods. Our extensive experimental evaluation shows the scalability exhibited by our proposed methods under various workload settings.