A contemporary combined approach for query expansion Dilip Kumar Sharma 1,2 & Rajendra Pamula 1 & D. S. Chauhan 2 Received: 15 February 2020 /Revised: 6 May 2020 /Accepted: 4 June 2020 # Springer Science+Business Media, LLC, part of Springer Nature 2020 Abstract The use of an automatic query expansion technique is to enhance the performance of the Information Retrieval System. Selecting the candidate terms for query expansion is an essential task to make query more precise to extract the most suitable documents. This paper provides a method to select the best terms for query enhancement. Firstly, the effect of abbreviation resolution, Lexical Variation, Synonyms, n-gram pseudo-relevance feed- back, Co-occurrence method on baseline approaches of query expansion is analyzed.. In this work, we used the Okapi BM25 algorithm for ranking. We used Concept-based normalization to deal with concept terms. Here our results show the improvement in results than the baseline approach. A new combined technique that integrates lexical variation, synonyms, n-gram pseudo relevance feedback for query enhancement is pro- posed. For experimental purpose three English written datasets CACM, CISI, and TREC-3 is used. The obtained results show improvement in the performance of query expansion concerning mean average precision, F-measure, and precision-recall curve. Keywords Query expansion . Pseudo-relevance feedback . Ontology on query expansion . Information retrieval system . Concept-based normalization Multimedia Tools and Applications https://doi.org/10.1007/s11042-020-09172-2 * Dilip Kumar Sharma todilipsharma@gmail.com Rajendra Pamula rajendrapamula@gmail.com D. S. Chauhan pdschauhan@gmail.com 1 Indian Institute of Technology(ISM), Dhanbad, India 2 GLA University, Mathura, India