mlsanityData to 7 Oct 2026

Query expansion techniques for information retrieval: A survey

arXiv 1708.00247 ↗First posted 1 Aug 2017cs.IRcited by 44

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Abstract (arXiv)

With the ever increasing size of the web, relevant information extraction on the Internet with a query formed by a few keywords has become a big challenge. Query Expansion (QE) plays a crucial role in improving searches on the Internet. Here, the user's initial query is reformulated by adding additional meaningful terms with similar significance. QE -- as part of information retrieval (IR) -- has long attracted researchers' attention. It has become very influential in the field of personalized social document, question answering, cross-language IR, information filtering and multimedia IR. Research in QE has gained further prominence because of IR dedicated conferences such as TREC (Text Information Retrieval Conference) and CLEF (Conference and Labs of the Evaluation Forum). This paper surveys QE techniques in IR from 1960 to 2017 with respect to core techniques, data sources used, weighting and ranking methodologies, user participation and applications -- bringing out similarities and differences.

Key facts. Cited by 44 papers in the map (data through 7 Oct 2026). First posted on arXiv 1 Aug 2017.

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Citing papers per year: 2021: 5; 2022: 3; 2023: 7; 2024: 8; 2025: 9; 2026: 12.

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  1. 2023Large Language Models for Information Retrieval: A Surveycited by 331
  2. 2026OpenResearcher: A Fully Open Pipeline for Long-Horizon Deep Research Trajectory Synthesiscited by 32
  3. 2023HyKGE: A Hypothesis Knowledge Graph Enhanced Framework for Accurate and Reliable Medical LLMs Responsescited by 25
  4. 2024Knowledge-Aware Query Expansion with Large Language Models for Textual and Relational Retrievalcited by 24
  5. 2024On Overcoming Miscalibrated Conversational Priors in LLM-based Chatbotscited by 23
  6. 2023MILL: Mutual Verification with Large Language Models for Zero-Shot Query Expansioncited by 22
  7. 2021Neural ranking models for document retrievalcited by 16
  8. 2024No Free Lunch: Retrieval-Augmented Generation Undermines Fairness in LLMs, Even for Vigilant Userscited by 9
  9. 2025A Survey on Retrieval And Structuring Augmented Generation with Large Language Modelscited by 8
  10. 2021Ultra-High Dimensional Sparse Representations with Binarization for Efficient Text Retrievalcited by 7
  11. 2021Privacy Policy Question Answering Assistant: A Query-Guided Extractive Summarization Approachcited by 5
  12. 2024Database-Augmented Query Representation for Information Retrievalcited by 5
32 more
  1. 2025Hybrid Retrieval for Hallucination Mitigation in Large Language Models: A Comparative Analysiscited by 5
  2. 2025Deep Literature Survey Automation with an Iterative Workflowcited by 5
  3. 2022Composite Code Sparse Autoencoders for first stage retrievalcited by 4
  4. 2023Relevance Feedback with Brain Signalscited by 4
  5. 2024Beyond Item Dissimilarities: Diversifying by Intent in Recommender Systemscited by 4
  6. 2025Leveraging LLM-Assisted Query Understanding for Live Retrieval-Augmented Generationcited by 4
  7. 2021GQE-PRF: Generative Query Expansion with Pseudo-Relevance Feedbackcited by 1
  8. 2022Modified Query Expansion Through Generative Adversarial Networks for Information Extraction in E-Commercecited by 1
  9. 2023Keyword Decisions in Sponsored Search Advertising: A Literature Review and Research Agendacited by 1
  10. 2024Aggregated Knowledge Model: Enhancing Domain-Specific QA with Fine-Tuned and Retrieval-Augmented Generation Modelscited by 1
  11. 2024A Survey of Query Optimization in Large Language Modelscited by 1
  12. 2025Single LLM, Multiple Roles: A Unified Retrieval-Augmented Generation Framework Using Role-Specific Token Optimizationcited by 1
  13. 2025KG-CQR: Leveraging Structured Relation Representations in Knowledge Graphs for Contextual Query Retrievalcited by 1
  14. 2026Rethinking RAG in Long Videos: What to Retrieve and How to Use It?cited by 1
  15. 2021Q4EDA: A Novel Strategy for Textual Information Retrieval Based on User Interactions with Visual Representations of Time Seriescited by 0
  16. 2022A Comparison of Approaches for Imbalanced Classification Problems in the Context of Retrieving Relevant Documents for an Analysiscited by 0
  17. 2023Robust Sentiment Analysis for Low Resource languages Using Data Augmentation Approaches: A Case Study in Marathicited by 0
  18. 2023Perturbation-based Active Learning for Question Answeringcited by 0
  19. 2024Adapting Dual-encoder Vision-language Models for Paraphrased Retrievalcited by 0
  20. 2025Multi-Modality Transformer for E-Commerce: Inferring User Purchase Intention to Bridge the Query-Product Gapcited by 0
  21. 2025GOLFer: Smaller LM-Generated Documents Hallucination Filter & Combiner for Query Expansion in Information Retrievalcited by 0
  22. 2025Ontology-Guided Query Expansion for Biomedical Document Retrieval using Large Language Modelscited by 0
  23. 2026QUARK: Robust Retrieval under Non-Faithful Queries via Query-Anchored Aggregationcited by 0
  24. 2026When should I search more: Adaptive Complex Query Optimization with Reinforcement Learningcited by 0
  25. 2026Efficient, Property-Aligned Fan-Out Retrieval via RL-Compiled Diffusioncited by 0
  26. 2026Finder: A Multimodal AI-Powered Search Framework for Pharmaceutical Data Retrievalcited by 0
  27. 2026Beyond Case Law: Evaluating Structure-Aware Retrieval and Safety in Statute-Centric Legal QAcited by 0
  28. 2026MVR-cache: Optimizing Semantic Caching via Multi-Vector Retrieval and Learned Prompt Segmentationcited by 0
  29. 2026DynaTree: Dynamic Agentic Retrieval Tree for Time-Sensitive News Retrievalcited by 0
  30. 2026STORM: Stepwise Token Optimization with Reward-Guided Beam Searchcited by 0
  31. 2026Staged Linguistic Seeding: Grounded Query Expansion for Verified-Unit QA in AI Contact Centerscited by 0
  32. 2026CHSR-RRF: A curriculum-gated hybrid retrieval framework with reciprocal rank fusion and leakage-aware benchmarking for educational RAGcited by 0