Evaluation of Hypothetical Document and Query Embeddings for Information Retrieval Enhancements in the Context of Diverse User Queries

Marten Jostmann () and Hendrik Winkelmann ()
Additional contact information
Marten Jostmann: viadee Unternehmensberatung AG
Hendrik Winkelmann: viadee Unternehmensberatung AG

A chapter in Shaping the Digital Future Through Innovation and Practice, 2026, pp 203-211 from Springer

Abstract: Abstract The task of Information Retrieval (IR) is the foundation of question-answering and information search systems. The complexity of these retrieval systems evolved to enable an effective search of a variety of documents based on users’ information needs. However, the quality of the retrieval results highly depends on the question phrasing and structure heavily influenced by the user’s age, expertise, background, and aim. This paper aims to close the gap between user-specific query structures and the content of various documents by employing the approaches Hypothetical Document Embeddings (HyDE) and Hypothetical Query Embeddings (HyQE). Both approaches achieve promising results in terms of effectiveness and robustness. An evaluation indicates that HyDE and HyQE outperform traditional retrieval methods such as BM25 and plain embedding methods.

Keywords: Information retrieval; Diverse queries; HyDE; HyQE (search for similar items in EconPapers)
Date: 2026
References: Add references at CitEc
Citations:

There are no downloads for this item, see the EconPapers FAQ for hints about obtaining it.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lnichp:978-3-032-08489-7_15

Ordering information: This item can be ordered from
http://www.springer.com/9783032084897

DOI: 10.1007/978-3-032-08489-7_15

Access Statistics for this chapter

More chapters in Lecture Notes in Information Systems and Organization from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().