A taxonomy of web search
Abstract
Classic IR (information retrieval) is inherently predicated on users searching for information, the so-called "information need". But the need behind a web search is often not informational -- it might be navigational (give me the url of the site I want to reach) or transactional (show me sites where I can perform a certain transaction, e.g. shop, download a file, or find a map). We explore this taxonomy of web searches and discuss how global search engines evolved to deal with web-specific needs.
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Prior studies of general-purpose search engines report that around 50% of queries are informational.
“Prior studies of general-purpose search engines report that around 50% of queries are informational (Broder, 2002).”
From DeepResearchGym: A Free, Transparent, and Reproducible Evaluation Sandbox for Deep Research (2025) · cites this paper as Broder, 2002
The way Broder developed the taxonomy of Web search could be used in the analysis of agent's information needs; the Cranfield paradigms widely used in TREC and NTCIR could serve as a starting point to inspire new ideas for AMM benchmark construction.
“For example, the way how Broder [8] developed the taxonomy of Web search could be used in the analysis of agent's information needs; the Crandfield paradigms widely used in TREC [65] and NTCIR [13] could serve as a starting point to inspire new ideas for AMM benchmark construction.”
From Agentic Memory Management Is the Next Frontier of Information Retrieval (2026) · cites this paper as [8]
Cites
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Who uses web search for what: and how
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Efficient PageRank approximation via graph aggregation
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Self-citationIntent classification of short-text on social media,
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Iannelli, M., & Ai, A. (2026) · arXiv · doi:10.48550/arxiv.2607.04282 · Cited by 2 · see citing works
DeepResearchGym: A Free, Transparent, and Reproducible Evaluation Sandbox for Deep Research
Coelho, J., Ning, J., He, J., Mao, K., Paladugu, A., Setlur, P., Jin, J., Callan, J., Magalhães, J., Martins, B., et al. (2025) · arXiv · doi:10.48550/arxiv.2505.19253 · Cited by 1 · see citing works
“Your task is to aggregate these points according to the following instructions:”
DeepResearchGym: A Free, Transparent, and Reproducible Sandbox for Deep Research
Coelho, J., Ning, J., He, J., Mao, K., Paladugu, A. S., Setlur, P., Jin, J., Callan, J., Magalhães, J., Martins, B., et al. (2026) · Proceedings of the 2026 International ACM SIGIR Conference on Innovative Concepts and Theories in Information Retrieval (ICTIR) · doi:10.1145/3805713.3820409
Gemini 1.5: Unlocking multimodal understanding across millions of tokens of context
Gemini Team, Georgiev, P., Lei, V. I., Burnell, R., Bai, L., Gulati, A., Tanzer, G., Vincent, D., Pan, Z., Wang, S., et al. (2024) · arXiv · doi:10.48550/arxiv.2403.05530 · Cited by 306 · see citing works
- Authors
- Broder, A.
- Affiliations
- IBM (United States) (US)
- Corresponding author
- Broder, Andrei
- ORCID
- Broder, Andrei
- Venue
- ACM SIGIR Forum
- Published
- 2002-09
- Volume
- 36
- Issue
- 2
- Pages
- 3-10
- ISSN
- 0163-5840 (ISSN-L)
- OpenAlex
- W2156037541
- Cited by
- 1,944
- References
- 1
- Citations by year
- 2026: 31 · 2025: 35 · 2024: 61 · 2023: 35 · 2022: 51 · 2021: 71 · 2020: 69 · 2019: 76 · 2018: 76 · 2017: 98 · 2016: 86 · 2015: 109 · 2014: 113 · 2013: 116 · 2012: 138
- FWCI
- 86.85
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- ACM SIGIR Forum (publishedVersion)
- Topics
- Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
- Physical Sciences › Computer Science › Information Systems › Web Data Mining and Analysis
- Physical Sciences › Computer Science › Information Systems › Recommender Systems and Techniques
- Keywords
- web search, information needs, search engine design
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