# Query expansion techniques for information retrieval: A survey

**Authors:** Hiteshwar Kumar Azad, Akshay Deepak  
**arXiv:** [1708.00247](https://arxiv.org/abs/1708.00247)  
**Date:** 2017-08-01  
**Summary page:** https://www.summarizepaper.com/en/paper/1708.00247v2/

## Key points

- Query expansion (QE) techniques in information retrieval (IR) have been studied from 1960 to 2017
- QE is important for improving searches on the Internet due to the vast amount of information and limited keywords
- The primary objective of QE is to add meaningful terms to a user's initial query
- QE has applications in personalized social document analysis, question answering systems, cross-language IR, information filtering, and multimedia IR
- Dedicated conferences like TREC and CLEF focus on IR and provide platforms for researchers to present findings on QE techniques
- The authors analyze QE techniques based on core methodologies, data sources used, weighting and ranking methodologies employed, user participation aspects, and applications
- The paper offers insights into the evolution of QE techniques over time and provides a comprehensive understanding of its applications in IR.

## Summary

This paper provides a comprehensive overview of query expansion (QE) techniques in the field of information retrieval (IR) from 1960 to 2017. The authors, Hiteshwar Kumar Azad and Akshay Deepak, highlight the significance of QE in improving searches on the Internet. With the ever-increasing size of the web and the challenge of extracting relevant information using only a few keywords, QE has become crucial for efficient information retrieval. The primary objective of QE is to reformulate a user's initial query by adding additional meaningful terms that have similar significance. This process has attracted significant attention from researchers and has found applications in various domains such as personalized social document analysis, question answering systems, cross-language IR, information filtering, and multimedia IR. The prominence of research in QE has been further enhanced by dedicated conferences like TREC (Text Information Retrieval Conference) and CLEF (Conference and Labs of the Evaluation Forum), which focus on IR. These conferences provide platforms for researchers to present their findings and exchange ideas related to QE techniques. In this survey paper, the authors analyze QE techniques based on core methodologies, data sources used, weighting and ranking methodologies employed, user participation aspects, and applications. By examining these factors across different studies conducted between 1960 and 2017, the authors aim to identify similarities and differences in QE approaches. The paper provides valuable insights into the evolution of QE techniques over time and offers a comprehensive understanding of its applications in IR. With its detailed analysis spanning several decades <fd>,</fd> this survey serves as a valuable resource for researchers interested in exploring or further advancing QE techniques for effective information retrieval.