Domain-specific information retrieval

Information Retrieval (IR) is much more than ad hoc web search: a large portion of the information-seeking activities takes place in specific domains, often addressing work-related tasks. Examples are lawyers finding relevant prior cases for a legal case and academic researchers studying the background material for a paper. In chapter 2, they outline the most common domain-specific tasks, data sets and applications. Domain-specific IR has a number of challenges that make set it apart from simple web search tasks: they often deal with long documents, long queries and long sessions with specific user needs. The authors discuss these in chapter 3. They also address issues related to the bias and fairness of models. In chapter 4, they describe the models and methods developed for domain-specific tasks and data, addressing the specific challenges, including user aspects related to domain-specific IR tasks, dealing with queries, user models and user interactions. They show that many of the methodological advances in domain-specific IR are transferable to other domains and even to open-domain web search. They conclude with the main takeaways and propose research directions for the near future.

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Publication Details

Journal
Foundations and Trends® in Information Retrieval
Published
2026-10-30
DOI
https://doi.org/10.1108/ftinr-09-2025-0088
Primary Topic
Information Retrieval and Search Behavior
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article
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article

Domain-specific information retrieval

Florina Piroi, Allan Hanbury, Suzan Verberne
Foundations and Trends® in Information Retrieval
Information Retrieval and Search Behavior
article

Domain-specific information retrieval

Florina Piroi, Allan Hanbury, Suzan Verberne
article en

Abstract

Information Retrieval (IR) is much more than ad hoc web search: a large portion of the information-seeking activities takes place in specific domains, often addressing work-related tasks. Examples are lawyers finding relevant prior cases for a legal case and academic researchers studying the background material for a paper. In chapter 2, they outline the most common domain-specific tasks, data sets and applications. Domain-specific IR has a number of challenges that make set it apart from simple web search tasks: they often deal with long documents, long queries and long sessions with specific user needs. The authors discuss these in chapter 3. They also address issues related to the bias and fairness of models. In chapter 4, they describe the models and methods developed for domain-specific tasks and data, addressing the specific challenges, including user aspects related to domain-specific IR tasks, dealing with queries, user models and user interactions. They show that many of the methodological advances in domain-specific IR are transferable to other domains and even to open-domain web search. They conclude with the main takeaways and propose research directions for the near future.

Foundations and Trends® in Information RetrievalVol. 20(5)
Leiden University (NL), TU Wien (AT), Complexity Science Hub (AT)
Openalex Percentile: Top 6%
Information Retrieval and Search Behavior
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Domain-specific information retrieval — Florina Piroi, Allan Hanbury, et al. · Foundations and Trends® in Information Retrieval (2026) | TGRS Research Map | TGRS