CoChat
Sign Up
Cited by 341Information Retrieval and Search BehaviorLibrary Science and Information LiteracyData Visualization and Analytics

The effects of domain knowledge on search tactic formulation

Wildemuth, Barbara M.·2004·Journal of the American Society for Information Science and Technology
DOI 10.1002/asi.10367
Open this paper in CoChat — free account

Abstract

A search tactic is a set of search moves that are temporally and semantically related. The current study examined the tactics of medical students searching a factual database in microbiology. The students answered problems and searched the database on three occasions over a 9‐month period. Their search moves were analyzed in terms of the changes in search terms used from one cycle to the next, using two different analysis methods. Common patterns were found in the students' search tactics; the most common approach was the specification of a concept, followed by the addition of one or more concepts, gradually narrowing the retrieved set before it was displayed. It was also found that the search tactics changed over time as the students' domain knowledge changed. These results have important implications for designers in developing systems that will support users' preferred ways of formulating searches. In addition, the research methods used (the coding scheme and the two data analysis methods—zero‐order state transition matrices and maximal repeating patterns [MRP] analysis) are discussed in terms of their validity in future studies of search tactics.

Integrity signals

Registry

Crossref · 10.1002/asi.10367

Cites

50 of 50 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

Claims the paper makes

This paper’s full text isn’t openly available, so its claims and self-check weren’t run. The registry and citation checks still apply.

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

  • Research in human-computer interaction characterizes user interaction patterns as structurally similar to human language, with latent structural patterns (a grammar) reflecting user strategies and preferences in performing routine tasks.

    “This work was inspired by research in human-computer interaction (HCI) that characterizes user interaction patterns as being structurally similar to human language, 8,53 with latent structural patterns - or a grammar - reflecting user strategies and preferences in performing routine tasks. 54,55”

    From A language model framework for sequence modeling of EHR audit logs to characterize clinician-EHR interactions (2026) · cites this paper as [54]

Cites

Flagged first, then by citations

Cited by

Sorted by citations

Related

Authors
Wildemuth, B. M.
Affiliations
University of North Carolina at Chapel Hill (US)
Corresponding author
Wildemuth, Barbara M.
Venue
Journal of the American Society for Information Science and Technology
Publisher
Wiley
Published
2003-11-13
Volume
55
Issue
3
Pages
246-258
ISSN
  • 1532-2882 (ISSN-L)
  • 1532-2890
DOI
10.1002/asi.10367
OpenAlex
W2126348911
Cited by
341
References
50
Citations by year
2026: 6 · 2025: 7 · 2024: 5 · 2023: 12 · 2022: 12 · 2021: 7 · 2020: 16 · 2019: 17 · 2018: 18 · 2017: 17 · 2016: 25 · 2015: 27 · 2014: 23 · 2013: 25 · 2012: 18
FWCI
22.84
Type
journal article
Language
en
Open access
closed
Licence
onlinelibrary.wiley.com/termsAndConditions#vor (vor)
Locations
Journal of the American Society for Information Science and Technology (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Information Systems › Information Retrieval and Search Behavior
  • Social Sciences › Library and Information Sciences › Library Science and Information Literacy
  • Physical Sciences › Computer Science › Computer Vision and Pattern Recognition › Data Visualization and Analytics
Keywords
search strategies, domain knowledge, medical students, factual databases, information seeking, state transition matrix, information retrieval

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review