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X Demographics
Mendeley readers
Attention Score in Context
| Title |
PubMed related articles: a probabilistic topic-based model for content similarity
|
|---|---|
| Published in |
BMC Bioinformatics, October 2007
|
| DOI | 10.1186/1471-2105-8-423 |
| Pubmed ID | |
| Authors |
Jimmy Lin, W John Wilbur |
| Abstract |
We present a probabilistic topic-based model for content similarity called pmra that underlies the related article search feature in PubMed. Whether or not a document is about a particular topic is computed from term frequencies, modeled as Poisson distributions. Unlike previous probabilistic retrieval models, we do not attempt to estimate relevance-but rather our focus is "relatedness", the probability that a user would want to examine a particular document given known interest in another. We also describe a novel technique for estimating parameters that does not require human relevance judgments; instead, the process is based on the existence of MeSH in MEDLINE. |
X Demographics
The data shown below were collected from the profiles of 4 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 25% |
| Australia | 1 | 25% |
| Japan | 1 | 25% |
| Unknown | 1 | 25% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 2 | 50% |
| Scientists | 2 | 50% |
Mendeley readers
The data shown below were compiled from readership statistics for 170 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 7 | 4% |
| United Kingdom | 7 | 4% |
| Netherlands | 2 | 1% |
| Switzerland | 2 | 1% |
| Germany | 1 | <1% |
| Ukraine | 1 | <1% |
| Slovenia | 1 | <1% |
| Canada | 1 | <1% |
| Denmark | 1 | <1% |
| Other | 1 | <1% |
| Unknown | 146 | 86% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 42 | 25% |
| Student > Ph. D. Student | 28 | 16% |
| Other | 19 | 11% |
| Student > Master | 15 | 9% |
| Professor | 10 | 6% |
| Other | 36 | 21% |
| Unknown | 20 | 12% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 61 | 36% |
| Medicine and Dentistry | 20 | 12% |
| Agricultural and Biological Sciences | 17 | 10% |
| Social Sciences | 13 | 8% |
| Business, Management and Accounting | 6 | 4% |
| Other | 26 | 15% |
| Unknown | 27 | 16% |
Attention Score in Context
This research output has an Altmetric Attention Score of 19. 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 19 May 2023.
All research outputs
#1,755,175
of 23,792,386 outputs
Outputs from BMC Bioinformatics
#375
of 7,439 outputs
Outputs of similar age
#3,768
of 77,957 outputs
Outputs of similar age from BMC Bioinformatics
#1
of 48 outputs
Altmetric has tracked 23,792,386 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 92nd percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 7,439 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.5. This one has done particularly well, scoring higher than 94% 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 77,957 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 95% of its contemporaries.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.