Colav Similairy
Package with customized colav similarity algorithm.
pip install hunahpu
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.
BSD-3-Clause License