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Information retrieval: Solving mismatching vocabulary in closed document collections.
- Source :
-
South African Journal of Libraries & Information Science . 2021, Vol. 87 Issue 2, p42-54. 13p. - Publication Year :
- 2021
-
Abstract
- During a search, phrase-terms expressed in queries are presented to an information retrieval system (IRS) to find documents relevant to a topic. The IRS makes relevance judgements by attempting to match vocabulary in queries to documents. If there is a mismatch, the problem of vocabulary mismatch occurs. The aim is to examine ways of searching for documents more effectively, in order to minimise mismatches. A further aim is to understand the mechanisms of, and the differences between, human and machine-assisted, retrieval. The objective of this study was to determine whether IRS-H (an IRS using the hybrid indexing method) and human participants agree or disagree on relevancy judgments, and whether the problem of mismatching vocabulary can be solved. A collection of eighty research documents and sixty-five phrase-terms were presented to (i) IRS-H and four participants in Test 1, and (ii) IRS-H and one participant (aided by search software) in Test 2. Statistical analysis was performed using the Kappa coefficient. IRS-H and the four participants' judgements disagreed. IRS-H and the participant aided by search software judgments did agree. IRS-H solves the problem of mismatching vocabulary between a query and a document. [ABSTRACT FROM AUTHOR]
- Subjects :
- *INFORMATION storage & retrieval systems
*INFORMATION retrieval
*VOCABULARY
Subjects
Details
- Language :
- English
- ISSN :
- 02568861
- Volume :
- 87
- Issue :
- 2
- Database :
- Academic Search Index
- Journal :
- South African Journal of Libraries & Information Science
- Publication Type :
- Academic Journal
- Accession number :
- 155353121
- Full Text :
- https://doi.org/10.7553/87-2-2106