TaxoSS 0.1.5

Semantic similarity computation with different state-of-the-art metrics

Semantic similarity computation with different state-of-the-art metrics

Description • Installation • Usage • License

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Description

TaxoSS is a semantic similarity library for Python which implements the state-of-the-art semantic similarity metrics like Resnik, JCN, and HSS.

Requirements

• Python 3.6 or later
• NLTK
• NumPy
• Pandas

Installation

TaxoSS can be installed through pip (the Python package manager) in the following way:

pip install taxoss

Usage

Semantic similarity functions

You can compute the semantic similarity in the following way:

from TaxoSS.functions import semantic_similarity
semantic_similarity('brother', 'sister', 'hss')

3.353513521371089

The function semantic_similarity(word1, word2, kind, ic) has these options for the argument kind:

• hss -> HSS (default)
• wup -> WUP
• lcs -> LC
• path_sim -> Shortest Path
• resnik -> Resnik
• jcn -> Jiang-Conrath
• lin -> Lin
• seco -> Seco

For the argument ic see the following section.

Information Content

Using a Wikipedia copus for calculating the Information Content (default of the argument ic):

from TaxoSS.functions import semantic_similarity
semantic_similarity('cat', 'dog', 'resnik')

6.169410755220327

Calculating Information Conent from a given corpus:

from TaxoSS.calculate_IC import calculate_IC
from TaxoSS.functions import semantic_similarity

calculate_IC(path_to_corpus, path_to_save_IC_file)
semantic_similarity('cat', 'dog', 'resnik', path_to_save_IC_file)

with path_to_save_IC_file a path into the virtual environment TaxoSS package, e.g. venv/lib/python3.6/site-packages/TaxoSS/data/prova_IC.csv.

Benchmark

	HSS (ours)	HSS (ours)	WUP	WUP	LC	LC	Shortest Path	Shortest Path	Resnik	Resnik	Jiang-Conrath	Jiang-Conrath	Lin	Lin	Seco	Seco
	Pearson	Spearman	Pearson	Spearman	Pearson	Spearman	Pearson	Spearman	Pearson	Spearman	Pearson	Spearman	Pearson	Spearman	Pearson	Spearman
MEN	0.41	0.33	0.36	0.33	0.14	0.05	0.07	0.03	0.05	0.03	-0.05	-0.04	0.05	0.04	-0.01	0.03
MC30	0.74	0.69	0.74	0.73	0.33	0.21	0.22	0.3	0.13	0.03	-0.06	-0.01	0.05	0.01	0.13	-0.09
WSS	0.68	0.65	0.58	0.59	0.36	0.23	0.16	0.1	0.02	-0.03	0.04	0.06	0.03	0.06	-0.01	-0.04
Simlex999	0.4	0.38	0.45	0.43	0.26	0.15	0.2	0.16	-0.04	-0.04	0.12	0.14	0.12	0.14	-0.02	-0.08
MT287	0.46	0.31	0.4	0.28	0.26	0.12	0.11	0.11	0.03	0.04	0.18	0.16	0.22	0.17	0	-0.06
MT771	0.44	0.4	0.43	0.49	0.06	0.02	0.1	0.13	0	-0.01	0	0	0	0	-0.05	-0.03
Time per pair (s)	0.0007	0.0007	0.008	0.008	0.0055	0.0055	0.0064	0.0064	0.5586	0.5586	0.551	0.551	0.5866	0.5866	0.0013	0.0013