Research Paper Journal of Information Science 1–13 Ó The Author(s) 2019 Article reuse guidelines: sagepub.com/journals-permissions DOI: 10.1177/0165551519863346 journals.sagepub.com/home/jis Real-time feedback query expansion technique for supporting scholarly search using citation network analysis Shah Khalid School of Computer Science and Communication Engineering, Jiangsu University, China; National University of Sciences and Technology (NUST), Pakistan Shengli Wu School of Computer Science and Communication Engineering, Jiangsu University, China Aftab Alam Department of Computer Science and Engineering, Kyung Hee University, South Korea Irfan Ullah Department of Computer Science, University of Peshawar, Pakistan Abstract Scholars routinely search relevant papers to discover and put a new idea into proper context. Despite ongoing advances in scholarly retrieval technologies, locating relevant papers through keyword queries is still quite challenging due to the massive expansion in the size of the research paper repository. To tackle this problem, we propose a novel real-time feedback query expansion technique, which is a two-stage interactive scholarly search process. Upon receiving the initial search query, the retrieval system provides a ranked list of results. In the second stage, a user selects a few relevant papers, from which useful terms are extracted for query expansion. The newly expanded query is run against the index in real time to generate the final list of research papers. In both stages, citation analysis is involved in further improving the quality of the results. The novelty of the approach lies in the combined exploitation of query expan- sion and citation analysis that may bring the most relevant papers to the top of the search results list. The experimental results on the Association of Computational Linguistics (ACL) Anthology Network data set demonstrate that this technique is effective and robust for locating relevant papers regarding normalised discounted cumulative gain (nDCG), precision and recall rates than several state-of- the-art approaches. Keywords Citation network analysis; query expansion; relevance feedback; scholarly search 1. Introduction This article addresses the problem of finding relevant papers that researchers face every day while using scholarly search engines on a given topic [1]. By harnessing the related work regarding a research topic, researchers aim to put new ideas into proper context. Therefore, they search, retrieve and understand the baseline approaches for their strength and weak- nesses. This results in new types of publications, and the process goes on resulting in a continuous process of recording the newly discovered information in scholarly databases for online accessibility around the globe [2]. However, the large Corresponding author: Shah Khalid, School of Computer Science and Communication Engineering, Jiangsu University, Zhenjiang, 212013, China. Email: shahkhalid@ujs.edu.cn