| Title |
On-Line Unsupervised Outlier Detection Using Finite Mixtures with Discounting Learning Algorithms
|
|---|---|
| Published in |
Data Mining and Knowledge Discovery, May 2004
|
| DOI | 10.1023/b:dami.0000023676.72185.7c |
| Authors |
Kenji Yamanishi, Jun-ichi Takeuchi, Graham Williams, Peter Milne |
Mendeley readers
The data shown below were compiled from readership statistics for 285 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 3 | 1% |
| Canada | 2 | <1% |
| Japan | 2 | <1% |
| United Kingdom | 2 | <1% |
| Brazil | 1 | <1% |
| Australia | 1 | <1% |
| Portugal | 1 | <1% |
| Belgium | 1 | <1% |
| Italy | 1 | <1% |
| Other | 2 | <1% |
| Unknown | 269 | 94% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 90 | 32% |
| Student > Master | 44 | 15% |
| Researcher | 29 | 10% |
| Student > Bachelor | 20 | 7% |
| Professor > Associate Professor | 19 | 7% |
| Other | 47 | 16% |
| Unknown | 36 | 13% |
| Readers by discipline | Count | As % |
|---|---|---|
| Computer Science | 149 | 52% |
| Engineering | 38 | 13% |
| Business, Management and Accounting | 16 | 6% |
| Mathematics | 13 | 5% |
| Agricultural and Biological Sciences | 4 | 1% |
| Other | 21 | 7% |
| Unknown | 44 | 15% |
Attention Score in Context
This research output has an Altmetric Attention Score of 9. 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 12 March 2024.
All research outputs
#3,798,287
of 25,371,288 outputs
Outputs from Data Mining and Knowledge Discovery
#51
of 637 outputs
Outputs of similar age
#6,440
of 62,291 outputs
Outputs of similar age from Data Mining and Knowledge Discovery
#1
of 1 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. Compared to these this one has done well and is in the 83rd percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 637 research outputs from this source. They receive a mean Attention Score of 3.7. This one has done particularly well, scoring higher than 91% 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 62,291 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 1 others from the same source and published within six weeks on either side of this one. This one has scored higher than all of them