The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.
RELEVANCE: A review of and a framework for the thinking on the notion in information science
Abstract
Information science emerged as the third subject, along with logic and philosophy, to deal with relevance‐an elusive, human notion. The concern with relevance, as a key notion in information science, is traced to the problems of scientific communication. Relevance is considered as a measure of the effectiveness of a contact between a source and a destination in a communication process. The different views of relevance that emerged are interpreted and related within a framework of communication of knowledge. Different views arose because relevance was considered at a number of different points in the process of knowledge communication. It is suggested that there exists an interlocking, interplaying cycle of various systems of relevances.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
The magical number seven, plus or minus two: Some limits on our capacity for processing information.
Miller, G. A. (1956) · Psychological Review · doi:10.1037/h0043158 · Cited by 17,812
Cited by
Perceived usefulness, perceived ease of use, and user acceptance of information technology
Davis, F. D. (1989) · MIS Quarterly · doi:10.2307/249008 · Cited by 68,483
Peer-review practices of psychological journals: The fate of published articles, submitted again
Peters, D. P., & Ceci, S. J. (1982) · Behavioral and Brain Sciences · doi:10.1017/s0140525x00011183 · Cited by 1,079
COGNITIVE PERSPECTIVES OF INFORMATION RETRIEVAL INTERACTION: ELEMENTS OF A COGNITIVE IR THEORY
INGWERSEN, P. (1996) · Journal of Documentation · doi:10.1108/eb026960 · Cited by 717
Test Collection Based Evaluation of Information Retrieval Systems
Sanderson, M. (2010) · Foundations and Trends® in Information Retrieval · doi:10.1561/1500000009 · Cited by 485
Teachers’ readiness and intention to teach artificial intelligence in schools
Ayanwale, M. A., Sanusi, I. T., Adelana, O. P., Aruleba, K. D., & Oyelere, S. S. (2022) · Computers and Education: Artificial Intelligence · doi:10.1016/j.caeai.2022.100099 · Cited by 412
Metadata
- Authors
- Saracevic, T.
- Venue
- Journal of the American Society for Information Science
- Publisher
- Wiley
- Published
- 1975-11
- Volume
- 26
- Issue
- 6
- Pages
- 321-343
- ISSN
- 0002-8231 (ISSN-L)
- 1097-4571
- OpenAlex
- W2092488901
- Cited by
- 863
- References
- 1
- FWCI
- 22.94
- Type
- journal article
- Language
- en
- Open access
- closed
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
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.