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

Related tags

Deep Learning TaxoSS
Overview

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

Description • Installation • Usage • License

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
You might also like...
A deep learning based semantic search platform that computes similarity scores between provided query and documents

semanticsearch This is a deep learning based semantic search platform that computes similarity scores between provided query and documents. Documents

null 1 Nov 30, 2021
Code for the CVPR2022 paper
Code for the CVPR2022 paper "Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity"

Introduction This is an official release of the paper "Frequency-driven Imperceptible Adversarial Attack on Semantic Similarity" (arxiv link). Abstrac

Leo 21 Nov 23, 2022
State of the Art Neural Networks for Deep Learning

pyradox This python library helps you with implementing various state of the art neural networks in a totally customizable fashion using Tensorflow 2

Ritvik Rastogi 60 May 29, 2022
Code for paper "A Critical Assessment of State-of-the-Art in Entity Alignment" (https://arxiv.org/abs/2010.16314)

A Critical Assessment of State-of-the-Art in Entity Alignment This repository contains the source code for the paper A Critical Assessment of State-of

Max Berrendorf 16 Oct 14, 2022
Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)
Quickly comparing your image classification models with the state-of-the-art models (such as DenseNet, ResNet, ...)

Image Classification Project Killer in PyTorch This repo is designed for those who want to start their experiments two days before the deadline and ki

null 349 Dec 8, 2022
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.
QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

QuickAI is a Python library that makes it extremely easy to experiment with state-of-the-art Machine Learning models.

null 152 Jan 2, 2023
LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models
LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models

LaneDet is an open source lane detection toolbox based on PyTorch that aims to pull together a wide variety of state-of-the-art lane detection models. Developers can reproduce these SOTA methods and build their own methods.

TuZheng 405 Jan 4, 2023
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.
tsai is an open-source deep learning package built on top of Pytorch & fastai focused on state-of-the-art techniques for time series classification, regression and forecasting.

Time series Timeseries Deep Learning Pytorch fastai - State-of-the-art Deep Learning with Time Series and Sequences in Pytorch / fastai

timeseriesAI 2.8k Jan 8, 2023
Deep Text Search is an AI-powered multilingual text search and recommendation engine with state-of-the-art transformer-based multilingual text embedding (50+ languages).
Deep Text Search is an AI-powered multilingual text search and recommendation engine with state-of-the-art transformer-based multilingual text embedding (50+ languages).

Deep Text Search - AI Based Text Search & Recommendation System Deep Text Search is an AI-powered multilingual text search and recommendation engine w

null 19 Sep 29, 2022
Owner
null
GitHub
The AugNet Python module contains functions for the fast computation of image similarity.

AugNet AugNet: End-to-End Unsupervised Visual Representation Learning with Image Augmentation arxiv link In our work, we propose AugNet, a new deep le

Ming 74 Dec 28, 2022
A PyTorch implementation of "SimGNN: A Neural Network Approach to Fast Graph Similarity Computation" (WSDM 2019).

SimGNN ⠀⠀⠀ A PyTorch implementation of SimGNN: A Neural Network Approach to Fast Graph Similarity Computation (WSDM 2019). Abstract Graph similarity s

Benedek Rozemberczki 534 Dec 25, 2022
We evaluate our method on different datasets (including ShapeNet, CUB-200-2011, and Pascal3D+) and achieve state-of-the-art results, outperforming all the other supervised and unsupervised methods and 3D representations, all in terms of performance, accuracy, and training time.

An Effective Loss Function for Generating 3D Models from Single 2D Image without Rendering Papers with code | Paper Nikola Zubić Pietro Lio University

Nikola Zubić 213 Dec 27, 2022
TorchMetrics is a collection of 25+ PyTorch metrics implementations and an easy-to-use API to create custom metrics.

Machine learning metrics for distributed, scalable PyTorch applications.

Pytorch Lightning 1.2k Jan 6, 2023
A curated list of awesome resources related to Semantic Search🔎 and Semantic Similarity tasks.

A curated list of awesome resources related to Semantic Search?? and Semantic Similarity tasks.

null 224 Jan 4, 2023
State of the art Semantic Sentence Embeddings

Contrastive Tension State of the art Semantic Sentence Embeddings Published Paper · Huggingface Models · Report Bug Overview This is the official code

Fredrik Carlsson 88 Dec 30, 2022
This is the unofficial code of Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes. which achieve state-of-the-art trade-off between accuracy and speed on cityscapes and camvid, without using inference acceleration and extra data

Deep Dual-resolution Networks for Real-time and Accurate Semantic Segmentation of Road Scenes Introduction This is the unofficial code of Deep Dual-re

chenjun 113 Dec 23, 2022
TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

TensorFlow Similarity is a python package focused on making similarity learning quick and easy.

null 912 Jan 8, 2023
Sharpened cosine similarity torch - A Sharpened Cosine Similarity layer for PyTorch

Sharpened Cosine Similarity A layer implementation for PyTorch Install At your c

Brandon Rohrer 203 Nov 30, 2022
[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

[NeurIPS 2021] A weak-shot object detection approach by transferring semantic similarity and mask prior.

BCMI 49 Jul 27, 2022