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X Demographics
Mendeley readers
Attention Score in Context
Chapter title |
Complex Symbolic Sequence Encodings for Predictive Monitoring of Business Processes
|
---|---|
Chapter number | 21 |
Book title |
Business Process Management
|
Published in |
Lecture notes in computer science, August 2015
|
DOI | 10.1007/978-3-319-23063-4_21 |
Book ISBNs |
978-3-31-923062-7, 978-3-31-923063-4
|
Authors |
Anna Leontjeva, Raffaele Conforti, Chiara Di Francescomarino, Marlon Dumas, Fabrizio Maria Maggi, Hamid Reza Motahari-Nezhad, Jan Recker, Matthias Weidlich, Leontjeva, Anna, Conforti, Raffaele, Di Francescomarino, Chiara, Dumas, Marlon, Maggi, Fabrizio Maria, Francescomarino, Chiara |
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 % |
---|---|---|
Estonia | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Scientists | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 112 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
Country | Count | As % |
---|---|---|
Germany | 1 | <1% |
Saudi Arabia | 1 | <1% |
Unknown | 110 | 98% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 34 | 30% |
Student > Master | 21 | 19% |
Researcher | 11 | 10% |
Student > Bachelor | 9 | 8% |
Student > Doctoral Student | 7 | 6% |
Other | 6 | 5% |
Unknown | 24 | 21% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 51 | 46% |
Business, Management and Accounting | 13 | 12% |
Engineering | 8 | 7% |
Economics, Econometrics and Finance | 5 | 4% |
Biochemistry, Genetics and Molecular Biology | 2 | 2% |
Other | 5 | 4% |
Unknown | 28 | 25% |
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 02 September 2015.
All research outputs
#18,425,370
of 22,826,360 outputs
Outputs from Lecture notes in computer science
#6,013
of 8,126 outputs
Outputs of similar age
#190,411
of 264,396 outputs
Outputs of similar age from Lecture notes in computer science
#128
of 300 outputs
Altmetric has tracked 22,826,360 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 8,126 research outputs from this source. They receive a mean Attention Score of 5.0. This one is in the 14th percentile – i.e., 14% 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 264,396 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 16th percentile – i.e., 16% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 300 others from the same source and published within six weeks on either side of this one. This one is in the 46th percentile – i.e., 46% of its contemporaries scored the same or lower than it.