An experiment examined how people use an online retrieval system. Subjects solved general topical search problems using a database containing the full text of news articles (e.g., find articles about the “Background of the new prime minister of Great Britain”). Time, accuracy and content of the searches were recorded. Of particular interest was the use of two iterative search methods available in the interface - a Lookup function that allowed users to explicitly specify an alternative query; and a LikeThese function that could be used to automatically generate a new query using articles the user marked as relevant. Results showed that subjects could easily use both query reformulation methods. Subjects generated much more effective LikeThese searches than Lookup searches. An analysis of individual subject differences suggests that the LikeThese method is more accessible to a wide range of users.
[1]
Richard A. Harshman,et al.
Indexing by Latent Semantic Analysis
,
1990,
J. Am. Soc. Inf. Sci..
[2]
Ruth B. Ekstrom,et al.
Manual for kit of factor-referenced cognitive tests
,
1976
.
[3]
Robert N. Oddy,et al.
INFORMATION RETRIEVAL THROUGH MAN‐MACHINE DIALOGUE
,
1977
.
[4]
Dennis E. Egan,et al.
Individual Differences In Human-Computer Interaction
,
1988
.
[5]
Craig Stanfill,et al.
Parallel free-text search on the connection machine system
,
1986,
CACM.
[6]
Michael David Williams,et al.
What Makes RABBIT Run?
,
1984,
Int. J. Man Mach. Stud..
[7]
Gerard Salton,et al.
Improving retrieval performance by relevance feedback
,
1997,
J. Am. Soc. Inf. Sci..
[8]
Susan T. Dumais,et al.
Using latent semantic analysis to improve information retrieval
,
1988,
CHI 1988.