Soft Computing Techniques Based Automatic Query Expansion Approach for Improving Document Retrieval

Automatic Query Expansion provides most suitable terms for retrieving relevant documents from datasets. In this paper, a new query expansion approach is proposed and implemented which is based on accelerated particle swarm optimization(PSO). Focus of the proposed technique is to find the most suitable expanded query in place of related expansion terms. The proposed technique uses Fuzzy logic to enhance the accuracy of accelerated particle swarm optimization with changing different parameters. The proposed technique is compared with another state of the art work on different performance parameters such as F-measure and Mean Average Precision. The efficiency of the proposed algorithm technique is also evaluated on two datasets as CACM and CISI. The results indicate that the proposed technique shows improved results compared to existing similar existing technique.

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