You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Evaluating the use of different positional strategies for sentence selection in biomedical literature summarization
|
|---|---|
| Published in |
BMC Bioinformatics, February 2013
|
| DOI | 10.1186/1471-2105-14-71 |
| Pubmed ID | |
| Authors |
Laura Plaza, Jorge Carrillo-de-Albornoz |
| Abstract |
The position of a sentence in a document has been traditionally considered an indicator of the relevance of the sentence, and therefore it is frequently used by automatic summarization systems as an attribute for sentence selection. Sentences close to the beginning of the document are supposed to deal with the main topic and thus are selected for the summary. This criterion has shown to be very effective when summarizing some types of documents, such as news items. However, this property is not likely to be found in other types of documents, such as scientific articles, where other positional criteria may be preferred. The purpose of the present work is to study the utility of different positional strategies for biomedical literature summarization. |
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 % |
|---|---|---|
| Norway | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 20 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Brazil | 1 | 5% |
| Unknown | 19 | 95% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 5 | 25% |
| Student > Doctoral Student | 3 | 15% |
| Student > Ph. D. Student | 3 | 15% |
| Student > Master | 3 | 15% |
| Lecturer | 2 | 10% |
| Other | 2 | 10% |
| Unknown | 2 | 10% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 12 | 60% |
| Agricultural and Biological Sciences | 2 | 10% |
| Psychology | 1 | 5% |
| Social Sciences | 1 | 5% |
| Unknown | 4 | 20% |
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 27 February 2013.
All research outputs
#20,184,694
of 22,699,621 outputs
Outputs from BMC Bioinformatics
#6,827
of 7,254 outputs
Outputs of similar age
#169,542
of 192,966 outputs
Outputs of similar age from BMC Bioinformatics
#152
of 159 outputs
Altmetric has tracked 22,699,621 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 7,254 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.4. This one is in the 1st percentile – i.e., 1% 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 192,966 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 159 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.