hanzi-stats

A homework asignment at https://ksi.ff.cuni.cz, subject Linguistic Analysis of Chinese.

https://github.com/stranak/hanzi-stats

Science Score: 44.0%

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    Low similarity (4.8%) to scientific vocabulary
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Repository

A homework asignment at https://ksi.ff.cuni.cz, subject Linguistic Analysis of Chinese.

Basic Info
  • Host: GitHub
  • Owner: stranak
  • License: mit
  • Language: Perl
  • Default Branch: master
  • Homepage:
  • Size: 131 KB
Statistics
  • Stars: 0
  • Watchers: 1
  • Forks: 0
  • Open Issues: 0
  • Releases: 0
Created about 4 years ago · Last pushed about 2 years ago
Metadata Files
Readme License Citation

README.md

HANZI stats

A homework asignment at https://ksi.ff.cuni.cz, subject Linguistic Analysis of Chinese.

Basic quantitative analysis of chinese characters and their aspects in a given text:

type/token ratio, frequencies of radicals, of characters with multiple pronounciations, etc. Most of the information I use is from Unicode Unihan. Resulting tables look like this.

All my code here is under MIT license.

cite as:

Straňák, P. Hanzi Stats [Computer software]. https://github.com/stranak/hanzi-stats .bibtex @software{Stranak_Hanzi_Stats, author = {Straňák, Pavel}, license = {MIT}, title = {{Hanzi Stats}}, url = {https://github.com/stranak/hanzi-stats} }

Owner

  • Name: Pavel Stranak
  • Login: stranak
  • Kind: user
  • Location: Praha
  • Company: Charles University

Citation (CITATION.cff)

# This CITATION.cff file was generated with cffinit.
# Visit https://bit.ly/cffinit to generate yours today!

cff-version: 1.2.0
title: Hanzi Stats
message: >-
  If you use this software, please cite it using the
  metadata from this file.
type: software
authors:
  - given-names: Pavel
    family-names: Straňák
    email: stranak@ufal.mff.cuni.cz
    affiliation: Charles University
    orcid: 'https://orcid.org/0000-0002-6895-8536'
repository-code: 'https://github.com/stranak/hanzi-stats'
abstract: >-
  Basic quantitative analysis of chinese characters and
  their aspects in a given text:


  type/token ratio, frequencies of radicals, of characters
  with multiple pronounciations, etc. Most of the
  information I use is from Unicode Unihan.
license: MIT
commit: 4111372eb940febd9c63b04a52c68e8afc277613

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