| Title |
Usability survey of biomedical question answering systems
|
|---|---|
| Published in |
Human Genomics, September 2012
|
| DOI | 10.1186/1479-7364-6-17 |
| Pubmed ID | |
| Authors |
Michael A Bauer, Daniel Berleant |
| Abstract |
We live in an age of access to more information than ever before. This can be a double-edged sword. Increased access to information allows for more informed and empowered researchers, while information overload becomes an increasingly serious risk. Thus, there is a need for intelligent information retrieval systems that can summarize relevant and reliable textual sources to satisfy a user's query. Question answering is a specialized type of information retrieval with the aim of returning precise short answers to queries posed as natural language questions. We present a review and comparison of three biomedical question answering systems: askHERMES (http://www.askhermes.org/), EAGLi (http://eagl.unige.ch/EAGLi/), and HONQA (http://services.hon.ch/cgi-bin/QA10/qa.pl). |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Argentina | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 47 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Australia | 1 | 2% |
| Unknown | 46 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 8 | 17% |
| Researcher | 8 | 17% |
| Student > Master | 6 | 13% |
| Professor | 4 | 9% |
| Other | 3 | 6% |
| Other | 7 | 15% |
| Unknown | 11 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 20 | 43% |
| Medicine and Dentistry | 3 | 6% |
| Engineering | 2 | 4% |
| Agricultural and Biological Sciences | 2 | 4% |
| Social Sciences | 2 | 4% |
| Other | 6 | 13% |
| Unknown | 12 | 26% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. 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 01 May 2013.
All research outputs
#20,656,820
of 25,374,647 outputs
Outputs from Human Genomics
#463
of 564 outputs
Outputs of similar age
#147,860
of 188,182 outputs
Outputs of similar age from Human Genomics
#5
of 5 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 10th percentile – i.e., 10% of other outputs scored the same or lower than it.
So far Altmetric has tracked 564 research outputs from this source. They typically receive more attention than average, with a mean Attention Score of 7.6. This one is in the 7th percentile – i.e., 7% of its peers scored the same or lower than it.
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 188,182 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 9th percentile – i.e., 9% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 5 others from the same source and published within six weeks on either side of this one.