Swarm optimized cluster based framework for information retrieval

作者：

Highlights：

• Integrated the power of swarm intelligence and data mining techniques to solve IR problem.

• Bio-inspired K-Flock algorithm is proposed for fuzzy clustering.

• Memory efficient RElim algorithm is used to extract closed frequent patterns.

• Probabilistic Document Retrieval Model is proposed for document retrieval.

• Proposed framework is examined on five varied size datasets.

摘要

•Integrated the power of swarm intelligence and data mining techniques to solve IR problem.•Bio-inspired K-Flock algorithm is proposed for fuzzy clustering.•Memory efficient RElim algorithm is used to extract closed frequent patterns.•Probabilistic Document Retrieval Model is proposed for document retrieval.•Proposed framework is examined on five varied size datasets.

论文关键词：Information retrieval,Swarm intelligence,Big data clustering,Frequent pattern mining,Unsupervised learning

论文评审过程：Received 15 April 2019, Revised 31 March 2020, Accepted 6 April 2020, Available online 11 April 2020, Version of Record 27 April 2020.

论文官网地址：https://doi.org/10.1016/j.eswa.2020.113441