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 |
Scaling associative classification for very large datasets
|
|---|---|
| Published in |
Journal of Big Data, December 2017
|
| DOI | 10.1186/s40537-017-0107-2 |
| Authors |
Luca Venturini, Elena Baralis, Paolo Garza |
X Demographics
The data shown below were collected from the profiles of 11 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 | 9% |
| Italy | 1 | 9% |
| Germany | 1 | 9% |
| Unknown | 8 | 73% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 10 | 91% |
| Science communicators (journalists, bloggers, editors) | 1 | 9% |
Mendeley readers
The data shown below were compiled from readership statistics for 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 5 | 16% |
| Researcher | 4 | 13% |
| Student > Doctoral Student | 4 | 13% |
| Student > Master | 3 | 10% |
| Student > Ph. D. Student | 3 | 10% |
| Other | 6 | 19% |
| Unknown | 6 | 19% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 14 | 45% |
| Engineering | 3 | 10% |
| Decision Sciences | 2 | 6% |
| Agricultural and Biological Sciences | 1 | 3% |
| Chemistry | 1 | 3% |
| Other | 1 | 3% |
| Unknown | 9 | 29% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. 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 18 August 2021.
All research outputs
#7,305,133
of 24,099,692 outputs
Outputs from Journal of Big Data
#125
of 364 outputs
Outputs of similar age
#138,674
of 447,286 outputs
Outputs of similar age from Journal of Big Data
#2
of 12 outputs
Altmetric has tracked 24,099,692 research outputs across all sources so far. This one has received more attention than most of these and is in the 69th percentile.
So far Altmetric has tracked 364 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.5. This one has gotten more attention than average, scoring higher than 65% 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 447,286 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 68% of its contemporaries.
We're also able to compare this research output to 12 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 91% of its contemporaries.