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Readability of Japanese Electronic Text with Phrase-based Line Breaking

Overview of attention for article published in Transactions of the Japanese Society of Artificial Intelligence, January 2015
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1 X user

Citations

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1 Dimensions

Readers on

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4 Mendeley
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Title
Readability of Japanese Electronic Text with Phrase-based Line Breaking
Published in
Transactions of the Japanese Society of Artificial Intelligence, January 2015
DOI 10.1527/tjsai.30.479
Authors

Jumpei Kobayashi, Takashi Sekiguchi, Eiji Shinbori, Toshio Kawashima

X Demographics

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.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 4 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Japan 1 25%
Unknown 3 75%

Demographic breakdown

Readers by professional status Count As %
Professor 1 25%
Student > Ph. D. Student 1 25%
Professor > Associate Professor 1 25%
Unknown 1 25%
Readers by discipline Count As %
Computer Science 2 50%
Design 1 25%
Unknown 1 25%
Attention Score in Context

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 08 December 2017.
All research outputs
#17,285,668
of 25,374,647 outputs
Outputs from Transactions of the Japanese Society of Artificial Intelligence
#136
of 227 outputs
Outputs of similar age
#220,161
of 359,528 outputs
Outputs of similar age from Transactions of the Japanese Society of Artificial Intelligence
#24
of 38 outputs
Altmetric has tracked 25,374,647 research outputs across all sources so far. This one is in the 21st percentile – i.e., 21% 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 is in the 18th percentile – i.e., 18% 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 359,528 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 29th percentile – i.e., 29% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 23rd percentile – i.e., 23% of its contemporaries scored the same or lower than it.