Data

Tools

Indexes

Applications

Experiments

Open Source Science

muldichinese

An open-source library in Python for analysing Chinese registers

https://github.com/nannan-liu/multidimensional-analysis-tagger-of-mandarin-chinese

Science Score: 49.0%

This score indicates how likely this project is to be science-related based on various indicators:

  • ○
    CITATION.cff file
  • ✓
    codemeta.json file
    Found codemeta.json file
  • ✓
    .zenodo.json file
    Found .zenodo.json file
  • ✓
    DOI references
    Found 3 DOI reference(s) in README
  • ✓
    Academic publication links
    Links to: acm.org
  • ○
    Academic email domains
  • ○
    Institutional organization owner
  • ○
    JOSS paper metadata
  • ○
    Scientific vocabulary similarity
    Low similarity (9.6%) to scientific vocabulary

Keywords

chinese chinese-nlp multidimensional python register
Last synced: 6 months ago · JSON representation

Repository

An open-source library in Python for analysing Chinese registers

Basic Info
  • Host: GitHub
  • Owner: Nannan-Liu
  • License: gpl-3.0
  • Language: Python
  • Default Branch: master
  • Homepage:
  • Size: 10 MB
Statistics
  • Stars: 3
  • Watchers: 1
  • Forks: 1
  • Open Issues: 0
  • Releases: 1
Topics
chinese chinese-nlp multidimensional python register
Created about 6 years ago · Last pushed almost 4 years ago
Metadata Files
Readme License Citation

README.md

Multidimensional-Analysis-Tagger-of-Mandarin-Chinese

MulDi Chinese (IPA: [ˌmʌl'daɪ] [ˌtʃaɪˈniːz]) is a multidimensional analysis tagger of Mandarin Chinese. - Installation: `pip install muldichinese`

About

Check the names of your input files, segment and pos tag the texts, and get the distribution of linguistic features and dimension scores of register variation from muldichinese.MulDiChinese import MulDiChinese mdc=MulDiChinese('/write/path/to/your/file(s)/') mdc.files() #print a list of your input files mdc.tag() #Segmentation and pos tagging completed. mdc.features() #Standardised frequencies of all 60 features written. mdc.dimensions() #Dimension scores written.

Reference the tagger

Liu, N. (2021). Multidimensional Analysis Tagger of Mandarin Chinese (Version 0.3.2). doi: 10.5281/zenodo.5220449.

This programme is based on the ICTCLAS, and it is advised to reference ICTCLAS when MulDi Chinese is used. Please refer to https://dl.acm.org/citation.cfm?id=1119280.

Requirements

Python packages needed are: 1. PyNLPIR 2. NLTK 3. Pandas 4. scikit learn 5. NumPy

See MulDi Chinese manual.pdf for more details

The manual contains a detailed description of the 60 features.

Owner

  • Name: Nannan Liu
  • Login: Nannan-Liu
  • Kind: user
  • Location: Italy
  • Company: University of Bologna

GitHub Events

Total
  • Watch event: 4
  • Create event: 1
Last Year
  • Watch event: 4
  • Create event: 1

Issues and Pull Requests

Last synced: over 1 year ago

All Time
  • Total issues: 0
  • Total pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Total issue authors: 0
  • Total pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
Past Year
  • Issues: 0
  • Pull requests: 0
  • Average time to close issues: N/A
  • Average time to close pull requests: N/A
  • Issue authors: 0
  • Pull request authors: 0
  • Average comments per issue: 0
  • Average comments per pull request: 0
  • Merged pull requests: 0
  • Bot issues: 0
  • Bot pull requests: 0
View more stats
Top Authors
Issue Authors
Pull Request Authors
Top Labels
Issue Labels
Pull Request Labels

Packages

  • Total packages: 1
  • Total downloads:
    • pypi 53 last-month
  • Total dependent packages: 0
  • Total dependent repositories: 1
  • Total versions: 18
  • Total maintainers: 1
pypi.org: muldichinese

A Chinese register analyser.

  • Versions: 18
  • Dependent Packages: 0
  • Dependent Repositories: 1
  • Downloads: 53 Last month
Rankings
Dependent packages count: 10.1%
Dependent repos count: 21.6%
Forks count: 22.6%
Average: 27.8%
Stargazers count: 38.8%
Downloads: 45.7%
Maintainers (1)
Nannan-Liu
Last synced: 6 months ago

Dependencies

setup.py pypi
  • PyNLPIR *
  • nltk *
  • numpy *
  • pandas *
  • scikit-learn *