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.
Twitter Demographics
Mendeley readers
Attention Score in Context
| Chapter title |
Data-Driven RDF Property Semantic-Equivalence Detection Using NLP Techniques
|
|---|---|
| Chapter number | 51 |
| Book title |
Knowledge Engineering and Knowledge Management
|
| Published in |
Lecture notes in computer science, November 2016
|
| DOI | 10.1007/978-3-319-49004-5_51 |
| Book ISBNs |
978-3-31-949003-8, 978-3-31-949004-5
|
| Authors |
Mariano Rico, Nandana Mihindukulasooriya, Asunción Gómez-Pérez |
| Editors |
Eva Blomqvist, Paolo Ciancarini, Francesco Poggi, Fabio Vitali |
Twitter Demographics
The data shown below were collected from the profiles of 5 tweeters who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Spain | 2 | 40% |
| Germany | 1 | 20% |
| United States | 1 | 20% |
| Unknown | 1 | 20% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 80% |
| Scientists | 1 | 20% |
Mendeley readers
The data shown below were compiled from readership statistics for 11 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 11 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Doctoral Student | 3 | 27% |
| Student > Ph. D. Student | 2 | 18% |
| Researcher | 2 | 18% |
| Student > Master | 1 | 9% |
| Professor > Associate Professor | 1 | 9% |
| Other | 0 | 0% |
| Unknown | 2 | 18% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 5 | 45% |
| Business, Management and Accounting | 1 | 9% |
| Unknown | 5 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 5. 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 November 2016.
All research outputs
#6,403,444
of 22,818,766 outputs
Outputs from Lecture notes in computer science
#2,096
of 8,124 outputs
Outputs of similar age
#98,342
of 311,238 outputs
Outputs of similar age from Lecture notes in computer science
#102
of 363 outputs
Altmetric has tracked 22,818,766 research outputs across all sources so far. This one has received more attention than most of these and is in the 71st percentile.
So far Altmetric has tracked 8,124 research outputs from this source. They receive a mean Attention Score of 5.0. This one has gotten more attention than average, scoring higher than 74% 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 311,238 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 363 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 72% of its contemporaries.