Hunahpu 0.0.5a0

Similarity metrics for bibliography

Hunahpu

Colav Similairy

Description

Package with customized colav similarity algorithm.

Installation

Package

pip install hunahpu

Usage

This is a library package, so you can use it in your code as follows:

from hunahpu.ColavSimilarity import ColavSimilarity

paper1 = {}
paper1['title'] = 'My title one'
paper1["journal"] = "Journal one"
paper1["year"] = 2016

paper2 = {}
paper2['title'] = 'My title two'
paper2["journal"] = "Jornal two"
paper2["year"] = 2016

if ColavSimilarity(paper1, paper2):
    print("The papers are similar")
else:
    print("The papers are not similar")

it also allows several options for tunning such as:

ratio_thold: int
    threshold for  ratio matric
partial_thold: int
    threshold for partial ratio
low_thold: int
    low threshold for ratios
use_translation : str
    enable translation support
use_parsing: boolean
    use parsing to remove unneeded characters 

example:

from hunahpu.ColavSimilarity import ColavSimilarity

paper1 = {}
paper1['title'] = 'My title one'
paper1["journal"] = "Journal one"
paper1["year"] = 2016

paper2 = {}
paper2['title'] = 'My title two'
paper2["journal"] = "Jornal two"
paper2["year"] = 2016

if ColavSimilarity(paper1, paper2, ratio_thold=90, partial_thold=92, low_thold=92, use_translation=True, use_parsing=True):
    print("The papers are similar")
else:
    print("The papers are not similar")

NOTE: translation does not work in all cases, so it is not recommended to use it.

License

BSD-3-Clause License

Links

http://colav.udea.edu.co/