↓ Skip to main content

Non-linear Similarity Learning for Semantic Compositionality

Overview of attention for article published in Transactions of the Japanese Society of Artificial Intelligence, January 2016
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (52nd percentile)

Mentioned by

twitter
3 X users

Readers on

mendeley
23 Mendeley
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.
Title
Non-linear Similarity Learning for Semantic Compositionality
Published in
Transactions of the Japanese Society of Artificial Intelligence, January 2016
DOI 10.1527/tjsai.o-fa2
Authors

Masashi Tsubaki, Masashi Shimbo, Yuji Matsumoto

X Demographics

X Demographics

The data shown below were collected from the profiles of 3 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 4%
Unknown 22 96%

Demographic breakdown

Readers by professional status Count As %
Student > Master 3 13%
Student > Bachelor 3 13%
Other 2 9%
Student > Ph. D. Student 1 4%
Researcher 1 4%
Other 0 0%
Unknown 13 57%
Readers by discipline Count As %
Computer Science 7 30%
Linguistics 1 4%
Neuroscience 1 4%
Unknown 14 61%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. 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 October 2017.
All research outputs
#15,168,167
of 25,371,288 outputs
Outputs from Transactions of the Japanese Society of Artificial Intelligence
#94
of 227 outputs
Outputs of similar age
#202,580
of 399,675 outputs
Outputs of similar age from Transactions of the Japanese Society of Artificial Intelligence
#7
of 19 outputs
Altmetric has tracked 25,371,288 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 227 research outputs from this source. They receive a mean Attention Score of 4.2. This one has gotten more attention than average, scoring higher than 55% 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 399,675 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 47th percentile – i.e., 47% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 19 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 52% of its contemporaries.