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Boolean versus ranked querying for biomedical systematic reviews

Overview of attention for article published in BMC Medical Informatics and Decision Making, October 2010
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About this Attention Score

  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (87th percentile)
  • High Attention Score compared to outputs of the same age and source (84th percentile)

Mentioned by

blogs
1 blog
twitter
2 tweeters

Citations

dimensions_citation
20 Dimensions

Readers on

mendeley
45 Mendeley
citeulike
1 CiteULike
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Title
Boolean versus ranked querying for biomedical systematic reviews
Published in
BMC Medical Informatics and Decision Making, October 2010
DOI 10.1186/1472-6947-10-58
Pubmed ID
Authors

Sarvnaz Karimi, Stefan Pohl, Falk Scholer, Lawrence Cavedon, Justin Zobel

Abstract

The process of constructing a systematic review, a document that compiles the published evidence pertaining to a specified medical topic, is intensely time-consuming, often taking a team of researchers over a year, with the identification of relevant published research comprising a substantial portion of the effort. The standard paradigm for this information-seeking task is to use Boolean search; however, this leaves the user(s) the requirement of examining every returned result. Further, our experience is that effective Boolean queries for this specific task are extremely difficult to formulate and typically require multiple iterations of refinement before being finalized.

Twitter Demographics

The data shown below were collected from the profiles of 2 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 45 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Canada 4 9%
United States 3 7%
United Kingdom 1 2%
Denmark 1 2%
Australia 1 2%
Unknown 35 78%

Demographic breakdown

Readers by professional status Count As %
Librarian 9 20%
Student > Ph. D. Student 9 20%
Student > Master 7 16%
Researcher 6 13%
Professor > Associate Professor 4 9%
Other 9 20%
Unknown 1 2%
Readers by discipline Count As %
Computer Science 16 36%
Medicine and Dentistry 10 22%
Social Sciences 6 13%
Agricultural and Biological Sciences 4 9%
Nursing and Health Professions 3 7%
Other 5 11%
Unknown 1 2%

Attention Score in Context

This research output has an Altmetric Attention Score of 10. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 29 July 2014.
All research outputs
#1,144,674
of 10,691,358 outputs
Outputs from BMC Medical Informatics and Decision Making
#116
of 1,044 outputs
Outputs of similar age
#23,906
of 185,685 outputs
Outputs of similar age from BMC Medical Informatics and Decision Making
#5
of 32 outputs
Altmetric has tracked 10,691,358 research outputs across all sources so far. Compared to these this one has done well and is in the 89th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,044 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 88% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 185,685 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 87% of its contemporaries.
We're also able to compare this research output to 32 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 84% of its contemporaries.